In this paper we describe the system proposed by NNI (NWPUNTU-I2R) team for the QUESST task within the Mediaeval 2014 evaluation. To solve the problem, we used both dynamic time warping (DTW) and symbolic search (SS) based approaches. The DTW system performs template matching using subsequence DTW algorithm and posterior representations. The symbolic search is performed on phone sequences generated by phone recognizers. For both symbolic and DTW search, partial sequence matching is performed to reduce missing rate, especially for query type 2 and 3. After fusing 9 DTW systems, 7 symbolic systems, and query length side information, we obtained 0.6023 actual normalized cross entropy (actCnxe) for all queries combined. For type 3 complex queries, we achieved 0.7252 actCnxe.
http://ceur-ws.org/Vol-1263/mediaeval2014_submission_69.pdf
Investigation of Text-to-Speech based Synthetic Parallel Data for Sequence-to...NU_I_TODALAB
APSIPA ASC 2021
Ding Ma, Wen-Chin Huang, Tomoki Toda: Investigation of text-to-speech-based synthetic parallel data for sequence-to-sequence non-parallel voice conversion, Dec. 2021
Toda Laboratory, Department of Intelligent Systems, Graduate School of Informatics, Nagoya University
Overview of the MediaEval 2014 Visual Privacy Task multimediaeval
This paper presents an overview of the Visual Privacy Task (VPT) of MediaEval 2014, its objectives, related dataset, and evaluation approaches. Participants in this task were required to implement a privacy filter or a combination of filters to protect various personal information regions in video sequences as provided. The
challenge was to achieve an adequate balance between the degree of privacy protection, intelligibility (how much useful information is retained post privacy filtering), and pleasantness (how minimal were the adverse effects of filtering on the appearance of the video frames). The submissions from the eight (8) teams who participated in this task were evaluated subjectively by surveillance experts, practitioners, data protection experts and by naïve viewers using a crowdsourcing approach.
http://ceur-ws.org/Vol-1263/mediaeval2014_submission_37.pdf
Stravinsqi/De Montfort University at the MediaEval 2014 C@merata Taskmultimediaeval
An overview is provided of the Stravinsqi-Jun2014 algorithm and its performance on the MediaEval 2014 C@merata Task. Stravinsqi stands for STaff Representation Analysed VIa Natural language String Query Input. The algorithm parses a symbolic representation of a piece of music as well as a query string consisting of a natural language expression, and identifies where event(s) specified by the query occur in the music. The output for any given query is a list of time windows corresponding to the locations of relevant events. To evaluate the algorithm, its output time windows are compared with those specified by music experts for the same query-piece combinations. In an evaluation consisting
of twenty pieces and 200 questions, Stravinsqi-Jun2014 had recall .91 and precision .46 at the measure level, and recall .87 and precision .44 at the beat level. Important potential applications of this work in music-educational software and musicological research are discussed.
http://ceur-ws.org/Vol-1263/mediaeval2014_submission_50.pdf
This paper provides an overview of the Social Event Detection (SED) system developed at LIMSI for the 2014 cam-
paign. Our approach is based on a hierarchical agglomera-
tive clustering that uses textual metadata, user-based knowl-
edge and geographical information. These dierent sources
of knowledge, either used separately or in cascade, reach
good results for the full clustering subtask with a normal-
ized mutual information equal to 0.95 and F1 scores greater
than 0.82 for our best run
Investigation of Text-to-Speech based Synthetic Parallel Data for Sequence-to...NU_I_TODALAB
APSIPA ASC 2021
Ding Ma, Wen-Chin Huang, Tomoki Toda: Investigation of text-to-speech-based synthetic parallel data for sequence-to-sequence non-parallel voice conversion, Dec. 2021
Toda Laboratory, Department of Intelligent Systems, Graduate School of Informatics, Nagoya University
Overview of the MediaEval 2014 Visual Privacy Task multimediaeval
This paper presents an overview of the Visual Privacy Task (VPT) of MediaEval 2014, its objectives, related dataset, and evaluation approaches. Participants in this task were required to implement a privacy filter or a combination of filters to protect various personal information regions in video sequences as provided. The
challenge was to achieve an adequate balance between the degree of privacy protection, intelligibility (how much useful information is retained post privacy filtering), and pleasantness (how minimal were the adverse effects of filtering on the appearance of the video frames). The submissions from the eight (8) teams who participated in this task were evaluated subjectively by surveillance experts, practitioners, data protection experts and by naïve viewers using a crowdsourcing approach.
http://ceur-ws.org/Vol-1263/mediaeval2014_submission_37.pdf
Stravinsqi/De Montfort University at the MediaEval 2014 C@merata Taskmultimediaeval
An overview is provided of the Stravinsqi-Jun2014 algorithm and its performance on the MediaEval 2014 C@merata Task. Stravinsqi stands for STaff Representation Analysed VIa Natural language String Query Input. The algorithm parses a symbolic representation of a piece of music as well as a query string consisting of a natural language expression, and identifies where event(s) specified by the query occur in the music. The output for any given query is a list of time windows corresponding to the locations of relevant events. To evaluate the algorithm, its output time windows are compared with those specified by music experts for the same query-piece combinations. In an evaluation consisting
of twenty pieces and 200 questions, Stravinsqi-Jun2014 had recall .91 and precision .46 at the measure level, and recall .87 and precision .44 at the beat level. Important potential applications of this work in music-educational software and musicological research are discussed.
http://ceur-ws.org/Vol-1263/mediaeval2014_submission_50.pdf
This paper provides an overview of the Social Event Detection (SED) system developed at LIMSI for the 2014 cam-
paign. Our approach is based on a hierarchical agglomera-
tive clustering that uses textual metadata, user-based knowl-
edge and geographical information. These dierent sources
of knowledge, either used separately or in cascade, reach
good results for the full clustering subtask with a normal-
ized mutual information equal to 0.95 and F1 scores greater
than 0.82 for our best run
4845 Programa de Embajadores Rotarios 2016 2017Miguel DE PAOLI
El Distrito 4845 de Argentina y Paraguay convocan a la selección de Team Leader y Team Members para participar del Programa de Embajadores Rotarios, quienes viajarán al Distrito 4060 de Kansas City en 2017
UNED @ Retrieving Diverse Social Images Taskmultimediaeval
This paper summarizes the participation of UNED at the 2014 Retrieving Diverse Social Images Task [3]. We propose a novel approach based on Formal Concept analysis (FCA) to detect the latent topics related to the images and a later Hierarchical Agglomerative Clustering (HAC) to put together the images according to these latent topics. The diversification will be based on offering images from the different topics detected. In order to detect these latent topics, two kinds of data have been tested: only information related to the description of the images and all the textual information related to the images. The results show that our proposal is suitable for search result diversification, achieving similar results to those in the state of the art.
http://ceur-ws.org/Vol-1263/mediaeval2014_submission_9.pdf
MediaEval 2014: THU-HCSIL Approach to Emotion in Music Task using Multi-level...multimediaeval
This working notes paper describes the system proposed by THU-HCSIL team for dynamic music emotion recognition. The procedure is divided into two module-feature extraction and regression. Both feature selection and feature combination are used to form the final THU feature set. In regression module, a Booster-based Multi-level Regression method is presented, which outperforms the baseline significantly on test data in RMSE metric for dynamic task.
http://ceur-ws.org/Vol-1263/mediaeval2014_submission_15.pdf
Synchronizing Multi-User Photo Galleries with MRFmultimediaeval
We present a novel solution to the MediaEval 2014 Event
Synchronization Task: Synchronization of Multi-User Event
Media (SEM). The framework is based on a probabilistic
graphical model. Thanks to the simple topology of the
graph, the estimation of the true temporal displacement
among multiple photo collections can be performed eciently
through exact inference. The underlying tness function is
dened in a exible way, for which it is possible to integrate
easily new information (e.g., text tags or social network
data). The exibility makes the framework suitable and
adaptable to cope with many real situations. The method
is evaluated on two datasets obtaining an overall accuracy
of more than 85% in both cases
TALP-UPC at MediaEval 2014 Placing Task: Combining Geographical Knowledge Bas...multimediaeval
This paper describes our Georeferencing approaches, experiments, and results at the MediaEval 2014 Placing Task evaluation. The task consists of predicting the most probable geographical coordinates of Flickr images and videos using its visual, audio and metadata associated features. Our approaches used only Flickr users textual metadata annotations and tagsets. We used four approaches for this task: 1) an approach based on Geographical Knowledge Bases (GeoKB), 2) the Hiemstra Language Model (HLM) approach with Re-Ranking, 3) a combination of the GeoKB and the HLM (GeoFusion). 4) a combination of the GeoFusion with a HLM model derived from the English Wikipedia georeferenced pages. The HLM approach with Re-Ranking showed the best performance within 10m to 1km distances. The GeoFusion approaches achieved the best results within the margin of errors from 10km to 5000km.
http://ceur-ws.org/Vol-1263/mediaeval2014_submission_77.pdf
The Search and Hyperlinking Task at MediaEval 2014multimediaeval
The Search and Hyperlinking Task at MediaEval 2014 is the third edition of this task. As in previous versions, it consisted of two sub-tasks: (i) answering search queries from a collection of roughly 2700 hours of BBC broadcast TV material, and (ii) linking anchor segments from within the videos to other target segments within the video collection. For MediaEval 2014, both sub-tasks were based on an ad-hoc retrieval scenario, and were evaluated using a pooling procedure across participants submissions with crowdsourcing relevance assessment using Amazon Mechanical Turk.
Emotional expression is an important property of music. Its
emotional characteristics are thus especially natural for
music indexing and recommendation. The Emotion in Music task addresses the task of automatic music emotion prediction and is held for the second year in 2014. As compared to previous year, we modified the task by offering a new feature development subtask, and releasing a new evaluation set. We employed a crowdsourcing approach to collect the data, using Amazon Mechanical Turk. The dataset consists of music licensed under Creative Commons from the Free Music Archive, which can be shared freely without restrictions. In this paper we describe the dataset collection, annotations, and evaluation criteria, as well as the two required and optional runs.
http://ceur-ws.org/Vol-1263/mediaeval2014_submission_33.pdf
T he SPL - IT Query by Example Search on Speech system for MediaEval 2014multimediaeval
This document briefly describes the system submitted by the Speech Processing Lab of Instituto de telecomunicações, pole of Coimbra (SPL-IT) to the Query by Example Search on Speech Task (QUESST) of MediaEval 2014. Our approach is based on merging results of a phoneme recognition system using three different languages. A version of Dynamic Time Warping (DTW) using posteriorgram distances was created to allow finding
some of the peculiar search cases of this task. Our primary submission merges two approaches: simple DTW
for detecting entire queries and a version where cutting final portions of queries is allowed. The late submission merges 5 approaches that account for all the search possibilities described for the task, though improved results
were only observed in the evaluation dataset for type 3 queries.
http://ceur-ws.org/Vol-1263/mediaeval2014_submission_74.pdf
This paper describes the results of the CERTH participation
in the Synchronization of Multi-User Event Media Task of
MediaEval 2014. We used a near duplicate image detector to identify very similar photos, which allowed us to temporally align photo galleries; and then we used time, geolocation and visual information, including the results of visual concept detection, to cluster all photos into different events.
http://ceur-ws.org/Vol-1263/mediaeval2014_submission_40.pdf
RECOD at MediaEval 2014: Violent Scenes Detection Taskmultimediaeval
This paper presents the RECOD approaches used in the MediaEval 2014 Violent Scenes Detection task. Our system is based on the combination of visual, audio, and text features. We also evaluate the performance of a convolutional network as a feature extractor. We combined those features using a fusion scheme. We participated in the main and the generalization tasks.
http://ceur-ws.org/Vol-1263/mediaeval2014_submission_89.pdf
The Munich LSTM-RNN Approach to the MediaEval 2014 “Emotion in Music” Taskmultimediaeval
In this paper we describe TUM's approach for the MediaEval's Emotion in Music" task. The goal of this task is to automatically estimate the emotions expressed by music (in terms of Arousal and Valence) in a time-continuous fashion. Our system consists of Long-Short Term Memory Recurrent Neural Networks (LSTM-RNN) for dynamic Arousal and Valence regression. We used two different sets of acoustic and psychoacoustic features that have been previously proven as effective for emotion prediction in music and speech. The best model yielded an average Pearson's correlation coeficient of 0.354 (Arousal) and 0.198 (Valence), and an average Root Mean Squared Error of 0.102 (Arousal) and 0.079 (Valence).
http://ceur-ws.org/Vol-1263/mediaeval2014_submission_7.pdf
MediaEval 2015 - The NNI Query-by-Example System for MediaEval 2015multimediaeval
This paper describes the system developed by the NNI team for the Query-by-Example Search on Speech Task (QUESST) in the MediaEval 2015 evaluation. Our submitted system mainly used bottleneck features/stacked bottleneck features (BNF/SBNF) trained from various resources. We investigated noise robustness techniques to deal with the noisy data of this year. The submitted system obtained the actual normalized cross entropy (actCnxe) of 0.761 and the actual Term Weighted Value (actTWV) of 0.270 on all types of queries of the evaluation data
http://ceur-ws.org/Vol-1436/
http://www.multimediaeval.org
Donald K. - Innovation in molecular diagnosis, next generation sequencing and...EuFMD
Session III
Accurate and rapid diagnostic tests are an essential component of initiatives to control and eradicate transboundary viral diseases such as foot-and-mouth disease (FMD). Tests are deployed to confirm initial cases of diseases, monitor the spread of the virus, characterise the causative viral strain, and to provide evidence of disease freedom after outbreaks. This presentation reviews progress to develop new diagnostic tools that can be used to detect and characterise viruses that cause important livestock diseases, including a “molecular toolbox” of new lineage-specific real-time RT-PCR assays that have been developed to quickly identify which FMDV lineage is present in samples. Away from laboratory testing, recent data demonstrates that simple sample preparation protocols and new equipment that utilize lyophilized reagents allow real-time RT-PCR or isothermal RT-LAMP assays to be performed in simple laboratories or in field settings in under 60 minutes.
A Novel, Robust, Hierarchical, Text-Independent Speaker Recognition TechniqueCSCJournals
Automatic speaker recognition system is used to recognize an unknown speaker among several reference speakers by making use of speaker-specific information from their speech. In this paper, we introduce a novel, hierarchical, text-independent speaker recognition. Our baseline speaker recognition system accuracy, built using statistical modeling techniques, gives an accuracy of 81% on the standard MIT database and our baseline gender recognition system gives an accuracy of 93.795%. We then propose and implement a novel state-space pruning technique by performing gender recognition before speaker recognition so as to improve the accuracy/timeliness of our baseline speaker recognition system. Based on the experiments conducted on the MIT database, we demonstrate that our proposed system improves the accuracy over the baseline system by approximately 2%, while reducing the computational time by more than 30%.
4845 Programa de Embajadores Rotarios 2016 2017Miguel DE PAOLI
El Distrito 4845 de Argentina y Paraguay convocan a la selección de Team Leader y Team Members para participar del Programa de Embajadores Rotarios, quienes viajarán al Distrito 4060 de Kansas City en 2017
UNED @ Retrieving Diverse Social Images Taskmultimediaeval
This paper summarizes the participation of UNED at the 2014 Retrieving Diverse Social Images Task [3]. We propose a novel approach based on Formal Concept analysis (FCA) to detect the latent topics related to the images and a later Hierarchical Agglomerative Clustering (HAC) to put together the images according to these latent topics. The diversification will be based on offering images from the different topics detected. In order to detect these latent topics, two kinds of data have been tested: only information related to the description of the images and all the textual information related to the images. The results show that our proposal is suitable for search result diversification, achieving similar results to those in the state of the art.
http://ceur-ws.org/Vol-1263/mediaeval2014_submission_9.pdf
MediaEval 2014: THU-HCSIL Approach to Emotion in Music Task using Multi-level...multimediaeval
This working notes paper describes the system proposed by THU-HCSIL team for dynamic music emotion recognition. The procedure is divided into two module-feature extraction and regression. Both feature selection and feature combination are used to form the final THU feature set. In regression module, a Booster-based Multi-level Regression method is presented, which outperforms the baseline significantly on test data in RMSE metric for dynamic task.
http://ceur-ws.org/Vol-1263/mediaeval2014_submission_15.pdf
Synchronizing Multi-User Photo Galleries with MRFmultimediaeval
We present a novel solution to the MediaEval 2014 Event
Synchronization Task: Synchronization of Multi-User Event
Media (SEM). The framework is based on a probabilistic
graphical model. Thanks to the simple topology of the
graph, the estimation of the true temporal displacement
among multiple photo collections can be performed eciently
through exact inference. The underlying tness function is
dened in a exible way, for which it is possible to integrate
easily new information (e.g., text tags or social network
data). The exibility makes the framework suitable and
adaptable to cope with many real situations. The method
is evaluated on two datasets obtaining an overall accuracy
of more than 85% in both cases
TALP-UPC at MediaEval 2014 Placing Task: Combining Geographical Knowledge Bas...multimediaeval
This paper describes our Georeferencing approaches, experiments, and results at the MediaEval 2014 Placing Task evaluation. The task consists of predicting the most probable geographical coordinates of Flickr images and videos using its visual, audio and metadata associated features. Our approaches used only Flickr users textual metadata annotations and tagsets. We used four approaches for this task: 1) an approach based on Geographical Knowledge Bases (GeoKB), 2) the Hiemstra Language Model (HLM) approach with Re-Ranking, 3) a combination of the GeoKB and the HLM (GeoFusion). 4) a combination of the GeoFusion with a HLM model derived from the English Wikipedia georeferenced pages. The HLM approach with Re-Ranking showed the best performance within 10m to 1km distances. The GeoFusion approaches achieved the best results within the margin of errors from 10km to 5000km.
http://ceur-ws.org/Vol-1263/mediaeval2014_submission_77.pdf
The Search and Hyperlinking Task at MediaEval 2014multimediaeval
The Search and Hyperlinking Task at MediaEval 2014 is the third edition of this task. As in previous versions, it consisted of two sub-tasks: (i) answering search queries from a collection of roughly 2700 hours of BBC broadcast TV material, and (ii) linking anchor segments from within the videos to other target segments within the video collection. For MediaEval 2014, both sub-tasks were based on an ad-hoc retrieval scenario, and were evaluated using a pooling procedure across participants submissions with crowdsourcing relevance assessment using Amazon Mechanical Turk.
Emotional expression is an important property of music. Its
emotional characteristics are thus especially natural for
music indexing and recommendation. The Emotion in Music task addresses the task of automatic music emotion prediction and is held for the second year in 2014. As compared to previous year, we modified the task by offering a new feature development subtask, and releasing a new evaluation set. We employed a crowdsourcing approach to collect the data, using Amazon Mechanical Turk. The dataset consists of music licensed under Creative Commons from the Free Music Archive, which can be shared freely without restrictions. In this paper we describe the dataset collection, annotations, and evaluation criteria, as well as the two required and optional runs.
http://ceur-ws.org/Vol-1263/mediaeval2014_submission_33.pdf
T he SPL - IT Query by Example Search on Speech system for MediaEval 2014multimediaeval
This document briefly describes the system submitted by the Speech Processing Lab of Instituto de telecomunicações, pole of Coimbra (SPL-IT) to the Query by Example Search on Speech Task (QUESST) of MediaEval 2014. Our approach is based on merging results of a phoneme recognition system using three different languages. A version of Dynamic Time Warping (DTW) using posteriorgram distances was created to allow finding
some of the peculiar search cases of this task. Our primary submission merges two approaches: simple DTW
for detecting entire queries and a version where cutting final portions of queries is allowed. The late submission merges 5 approaches that account for all the search possibilities described for the task, though improved results
were only observed in the evaluation dataset for type 3 queries.
http://ceur-ws.org/Vol-1263/mediaeval2014_submission_74.pdf
This paper describes the results of the CERTH participation
in the Synchronization of Multi-User Event Media Task of
MediaEval 2014. We used a near duplicate image detector to identify very similar photos, which allowed us to temporally align photo galleries; and then we used time, geolocation and visual information, including the results of visual concept detection, to cluster all photos into different events.
http://ceur-ws.org/Vol-1263/mediaeval2014_submission_40.pdf
RECOD at MediaEval 2014: Violent Scenes Detection Taskmultimediaeval
This paper presents the RECOD approaches used in the MediaEval 2014 Violent Scenes Detection task. Our system is based on the combination of visual, audio, and text features. We also evaluate the performance of a convolutional network as a feature extractor. We combined those features using a fusion scheme. We participated in the main and the generalization tasks.
http://ceur-ws.org/Vol-1263/mediaeval2014_submission_89.pdf
The Munich LSTM-RNN Approach to the MediaEval 2014 “Emotion in Music” Taskmultimediaeval
In this paper we describe TUM's approach for the MediaEval's Emotion in Music" task. The goal of this task is to automatically estimate the emotions expressed by music (in terms of Arousal and Valence) in a time-continuous fashion. Our system consists of Long-Short Term Memory Recurrent Neural Networks (LSTM-RNN) for dynamic Arousal and Valence regression. We used two different sets of acoustic and psychoacoustic features that have been previously proven as effective for emotion prediction in music and speech. The best model yielded an average Pearson's correlation coeficient of 0.354 (Arousal) and 0.198 (Valence), and an average Root Mean Squared Error of 0.102 (Arousal) and 0.079 (Valence).
http://ceur-ws.org/Vol-1263/mediaeval2014_submission_7.pdf
MediaEval 2015 - The NNI Query-by-Example System for MediaEval 2015multimediaeval
This paper describes the system developed by the NNI team for the Query-by-Example Search on Speech Task (QUESST) in the MediaEval 2015 evaluation. Our submitted system mainly used bottleneck features/stacked bottleneck features (BNF/SBNF) trained from various resources. We investigated noise robustness techniques to deal with the noisy data of this year. The submitted system obtained the actual normalized cross entropy (actCnxe) of 0.761 and the actual Term Weighted Value (actTWV) of 0.270 on all types of queries of the evaluation data
http://ceur-ws.org/Vol-1436/
http://www.multimediaeval.org
Donald K. - Innovation in molecular diagnosis, next generation sequencing and...EuFMD
Session III
Accurate and rapid diagnostic tests are an essential component of initiatives to control and eradicate transboundary viral diseases such as foot-and-mouth disease (FMD). Tests are deployed to confirm initial cases of diseases, monitor the spread of the virus, characterise the causative viral strain, and to provide evidence of disease freedom after outbreaks. This presentation reviews progress to develop new diagnostic tools that can be used to detect and characterise viruses that cause important livestock diseases, including a “molecular toolbox” of new lineage-specific real-time RT-PCR assays that have been developed to quickly identify which FMDV lineage is present in samples. Away from laboratory testing, recent data demonstrates that simple sample preparation protocols and new equipment that utilize lyophilized reagents allow real-time RT-PCR or isothermal RT-LAMP assays to be performed in simple laboratories or in field settings in under 60 minutes.
A Novel, Robust, Hierarchical, Text-Independent Speaker Recognition TechniqueCSCJournals
Automatic speaker recognition system is used to recognize an unknown speaker among several reference speakers by making use of speaker-specific information from their speech. In this paper, we introduce a novel, hierarchical, text-independent speaker recognition. Our baseline speaker recognition system accuracy, built using statistical modeling techniques, gives an accuracy of 81% on the standard MIT database and our baseline gender recognition system gives an accuracy of 93.795%. We then propose and implement a novel state-space pruning technique by performing gender recognition before speaker recognition so as to improve the accuracy/timeliness of our baseline speaker recognition system. Based on the experiments conducted on the MIT database, we demonstrate that our proposed system improves the accuracy over the baseline system by approximately 2%, while reducing the computational time by more than 30%.
Classification of Strokes in Table Tennis with a Three Stream Spatio-Temporal...multimediaeval
Paper: http://ceur-ws.org/Vol-2882/paper62.pdf
YouTube: https://youtu.be/gV-rvV3iFDA
Pierre-Etienne Martin, Jenny Benois-Pineau, Boris Mansencal, Renaud Péteri and Julien Morlier : Classification of Strokes in Table Tennis with a Three Stream Spatio-Temporal CNN for MediaEval 2020. Proc. of MediaEval 2020, 14-15 December 2020, Online.
This work presents a method for classifying table tennis strokes using spatio-temporal convolutional neural networks. The fine-grained classification is performed on trimmed video segments recorded at 120 fps with different players performing in natural conditions. From those segments, the frames are extracted, their optical flow is computed and the pose of the player is estimated. From the optical flow amplitude, a region of interest is inferred. A three stream spatio-temporal convolutional neural network using combination of those modalities and 3D attention mechanisms is presented in order to perform classification.
Presented by: Pierre-Etienne Martin
HCMUS at MediaEval 2020: Ensembles of Temporal Deep Neural Networks for Table...multimediaeval
Paper: http://ceur-ws.org/Vol-2882/paper50.pdf
Hai Nguyen-Truong, San Cao, N. A. Khoa Nguyen, Bang-Dang Pham, Hieu Dao, Minh-Quan Le, Hoang-Phuc Nguyen-Dinh, Hai-Dang Nguyen and Minh-Triet Tran : HCMUS at MediaEval 2020: Ensembles of Temporal Deep Neural Networks for Table Tennis Strokes Classification Task. Proc. of MediaEval 2020, 14-15 December 2020, Online.
The Sports Video Classification Tasks in the Multimedia Evaluation 2020 Challenge focuses on classifying different types of table tennis strokes in video segments. In this task, we - the HCMUS Team - perform multiple experiments, which includes a combination of models such as SlowFast, Optical Flow, DensePose, R2+1, Channel-Separated Convolutional Networks, to classify 21 types of table tennis strokes from video segments. In total, we submit eight runs corresponding to five different models with different sets of hyper-parameters in each of our models. In addition, we apply some pre-processing techniques on the dataset in order for our model to learn and classify more accurately. According to the evaluation results, one of our team's methods out-performs the other team's. In particular, our best run achieves 31.35\% global accuracy, and all of our methods show potential results in terms of local and global accuracy for action recognition tasks.
Sports Video Classification: Classification of Strokes in Table Tennis for Me...multimediaeval
Paper: http://ceur-ws.org/Vol-2882/paper2.pdf
YouTube: https://youtu.be/-bRL868b8ys
Pierre-Etienne Martin, Jenny Benois-Pineau, Boris Mansencal, Renaud Péteri, Laurent Mascarilla, Jordan Calandre and Julien Morlier : Sports Video Classification: Classification of Strokes in Table Tennis for MediaEval 2020. Proc. of MediaEval 2020, 14-15 December 2020, Online.
Fine-grained action classification has raised new challenges compared to classical action classification problems. Sport video analysis is a very popular research topic, due to the variety of application areas, ranging from multimedia intelligent devices with user-tailored digests, up to analysis of athletes' performances. Running since 2019 as a part of MediaEval, we offer a task which consists in classifying table tennis strokes from videos recorded in natural conditions at the University of Bordeaux. The aim is to build tools for teachers, coaches and players to analyse table tennis games. Such tools could lead to an automatic profiling of the player and adaptation of his training for improving his/her sport skills more efficiently.
Presented by: Pierre-Etienne Martin
Predicting Media Memorability from a Multimodal Late Fusion of Self-Attention...multimediaeval
Paper: http://ceur-ws.org/Vol-2882/paper61.pdf
YouTube: https://youtu.be/brmI4g3jLS4
Ricardo Kleinlein, Cristina Luna-Jiménez, Fernando Fernández-Martínez and Zoraida Callejas : Predicting Media Memorability from a Multimodal Late Fusion of Self-Attention and LSTM Models. Proc. of MediaEval 2020, 14-15 December 2020, Online.
This paper reports on the GTH-UPM team experience in the Predicting Media Memorability task at MediaEval 2020. Teams were requested to predict memorability scores at both short-term and long-term, understanding such score as a measure of whether a video was perdurable in a viewer's memory or not. Our proposed system relies on a late fusion of the scores predicted by three sequential models, each trained over a different modality: video captions, aural embeddings and visual optical flow-based vectors. Whereas single-modality models show a low or zero Spearman correlation coefficient value, their combination considerably boosts performance over development data up to 0.2 in the short-term memorability prediction subtask and 0.19 in the long-term subtask. However, performance over test data drops to 0.016 and -0.041, respectively.
Presented by: Ricardo Kleinlein
Essex-NLIP at MediaEval Predicting Media Memorability 2020 Taskmultimediaeval
Paper: http://ceur-ws.org/Vol-2882/paper52.pdf
Janadhip Jacutprakart, Rukiye Savran Kiziltepe, John Q. Gan, Giorgos Papanastasiou and Alba G. Seco de Herrera : Essex-NLIP at MediaEval Predicting Media Memorability 2020 Task. Proc. of MediaEval 2020, 14-15 December 2020, Online.
In this paper, we present the methods of approach and the main results from the Essex NLIP Team’s participation in the MediEval 2020 Predicting Media Memorability task. The task requires participants to build systems that can predict short-term and long-term memorability scores on real-world video samples provided. The focus of our approach is on the use of colour-based visual features as well as the use of the video annotation meta-data. In addition, hyper-parameter tuning was explored. Besides the simplicity of the methodology, our approach achieves competitive results. We investigated the use of different visual features. We assessed the performance of memorability scores through various regression models where Random Forest regression is our final model, to predict the memorability of videos.
Overview of MediaEval 2020 Predicting Media Memorability task: What Makes a V...multimediaeval
Paper: http://ceur-ws.org/Vol-2882/paper6.pdf
YouTube: https://youtu.be/ySGGu_4vaxs
Alba García Seco De Herrera, Rukiye Savran Kiziltepe, Jon Chamberlain, Mihai Gabriel Constantin, Claire-Hélène Demarty, Faiyaz Doctor, Bogdan Ionescu and Alan F. Smeaton : Overview of MediaEval 2020 Predicting Media Memorability task: What Makes a Video Memorable? Proc. of MediaEval 2020, 14-15 December 2020, Online.
This paper describes the MediaEval 2020 Predicting Media Memorability task. After first being proposed at MediaEval 2018, the Predicting Media Memorability task is in its 3rd edition this year, as the prediction of short-term and long-term video memorability (VM) remains a challenging task. In 2020, the format remained the same as in previous editions. This year the videos are a subset of the TRECVid 2019 Video to Text dataset, containing more action rich video content as compare with the 2019 task. In this paper a description of some aspects of this task is provided, including its main characteristics, a description of the collection, the ground truth dataset, evaluation metrics and the requirements for the run submission.
Presented by: Rukiye Savran Kiziltepe
Fooling an Automatic Image Quality Estimatormultimediaeval
Paper: http://ceur-ws.org/Vol-2882/paper45.pdf
Benoit Bonnet, Teddy Furon and Patrick Bas : Fooling an Automatic Image Quality Estimator. Proc. of MediaEval 2020, 14-15 December 2020, Online.
In this paper we present our work on the 2020 MediaEval task: Pixel "Privacy: Quality Camouflage for Social Images". Blind Image Quality Assessment (BIQA) is a classifier that for any given image will return a quality score. Our task is to modify an image to decrease its BIQA score while maintaining a good perceived quality. Since BIQA is a deep neural network, we worked on an adversarial attack approach of the problem.
Fooling Blind Image Quality Assessment by Optimizing a Human-Understandable C...multimediaeval
Paper: http://ceur-ws.org/Vol-2882/paper16.pdf
YouTube: https://youtu.be/ix_b9K7j72w
Zhengyu Zhao : Fooling Blind Image Quality Assessment by Optimizing a Human-Understandable Color Filter. Proc. of MediaEval 2020, 14-15 December 2020, Online.
This paper presents the submission of our RU-DS team to the Pixel Privacy Task 2020. We propose to fool the blind image quality assessment model by transforming images based on optimizing a human-understandable color filter. In contrast to the common work that relies on small, $L_p$-bounded additive pixel perturbations, our approach yields large yet smooth perturbations. Experimental results demonstrate that in the specific context of this task, our approach is able to achieve strong adversarial effects, but has to sacrifice the image appeal.
Presented by: Zhengyu Zhao
Pixel Privacy: Quality Camouflage for Social Imagesmultimediaeval
Paper: http://ceur-ws.org/Vol-2882/paper77.pdf
YouTube: https://youtu.be/8Rr4KknGSac
Zhuoran Liu, Zhengyu Zhao, Martha Larson and Laurent Amsaleg : Pixel Privacy: Quality Camouflage for Social Images. Proc. of MediaEval 2020, 14-15 December 2020, Online.
High-quality social images shared online can be misappropriated for unauthorized goals, where the quality filtering step is commonly carried out by automatic Blind Image Quality Assessment (BIQA) algorithms. Pixel Privacy benchmarks privacy-protective approaches that protect privacy-sensitive images against unethical computer vision algorithms. In the 2020 task, participants are encouraged to develop camouflage methods that can effectively decrease the BIQA quality score of high-quality images and maintain image appeal. The camouflaged images need to be either imperceptible to the human eye, or it can be a visible enhancement.
Presented by: Zhuoran Liu
HCMUS at MediaEval 2020:Image-Text Fusion for Automatic News-Images Re-Matchingmultimediaeval
Paper: http://ceur-ws.org/Vol-2882/paper73.pdf
YouTube: https://youtu.be/TadJ6y7xZeA
Thuc Nguyen-Quang, Tuan-Duy Nguyen, Thang-Long Nguyen-Ho, Anh-Kiet Duong, Xuan-Nhat Hoang, Vinh-Thuyen Nguyen-Truong, Hai-Dang Nguyen and Minh-Triet Tran : HCMUS at MediaEval 2020:Image-Text Fusion for Automatic News-Images Re-Matching. Proc. of MediaEval 2020, 14-15 December 2020, Online.
Matching text and images based on their semantics has an important role in cross-media retrieval. However, text and images in articles have a complex connection. In the context of MediaEval 2020 Challenge, we propose three multi-modal methods for mapping text and images of news articles to the shared space in order to perform efficient cross-retrieval. Our methods show systemic improvement and validate our hypotheses, while the best-performed method reaches a recall@100 score of 0.2064.
Presented by: Thuc Nguyen-Quang
Efficient Supervision Net: Polyp Segmentation using EfficientNet and Attentio...multimediaeval
Paper: http://ceur-ws.org/Vol-2882/paper72.pdf
Sabarinathan D and Suganya Ramamoorthy : Efficient Supervision Net: Polyp Segmentation using EfficientNet and Attention Unit. Proc. of MediaEval 2020, 14-15 December 2020, Online.
Colorectal cancer is the third most common cause of cancer worldwide. In the era of medical Industry, identifying colorectal cancer in its early stages has been a challenging problem. Inspired by these issues, the main objective of this paper is to develop a Multi supervision net algorithm for segmenting polys on a comprehensive dataset. The risk of colorectal cancer could be reduced by early diagnosis of poly during a colonoscopy. The disease and their symptoms are highly varying and always a need for a continuous update of knowledge for the doctors and medical analyst. The diseases fall into different categories and a small variation of symptoms may lead to higher rate of risk. We have taken Medico polyp challenge dataset, which consists of 1000 segmented polyp images from gastrointestinal track. We proposed an efficient Net B4 as a pre-trained architecture in multi-supervision net. The model is trained with multiple output layers. We present quantitative results on colorectal dataset to evaluate the performance and achieved good results in all the performance metrics. The experimental results proved that the proposed model is robust and provides a good level of accuracy in segmenting polyps on a comprehensive dataset for different metrics such as Dice coefficient, Recall, Precision and F2.
HCMUS at Medico Automatic Polyp Segmentation Task 2020: PraNet and ResUnet++ ...multimediaeval
Paper: http://ceur-ws.org/Vol-2882/paper47.pdf
YouTube: https://youtu.be/vMsM4zg2-JY
Tien-Phat Nguyen, Tan-Cong Nguyen, Gia-Han Diep, Minh-Quan Le, Hoang-Phuc Nguyen-Dinh, Hai-Dang Nguyen and Minh-Triet Tran : HCMUS at Medico Automatic Polyp Segmentation Task 2020: PraNet and ResUnet++ for Polyps Segmentation. Proc. of MediaEval 2020, 14-15 December 2020, Online.
The Medico task, MediaEval 2020, explores the challenge of building accurate and high-performance algorithms to detect all types of polyps in endoscopic images. We proposed different approaches leveraging the advantages of either ResUnet++ or PraNet model to efficiently segment polyps in colonoscopy images, with modifications on the network structure, parameters, and training strategies to tackle various observed characteristics of the given dataset. Our methods outperform the other teams' methods, for both accuracy and efficiency. After the evaluation, we are at top 2 for task 1 (with Jaccard index of 0.777, best Precision and Accuracy scores) and top 1 for task 2 (with 67.52 FPS and Jaccard index of 0.658).
Depth-wise Separable Atrous Convolution for Polyps Segmentation in Gastro-Int...multimediaeval
Paper: http://ceur-ws.org/Vol-2882/paper31.pdf
Syed Muhammad Faraz Ali, Muhammad Taha Khan, Syed Unaiz Haider, Talha Ahmed, Zeshan Khan and Muhammad Atif Tahir : Depth-wise Separable Atrous Convolution for Polyps Segmentation in Gastro-Intestinal Tract. Proc. of MediaEval 2020, 14-15 December 2020, Online.
Identification of polyps in endoscopic images is critical for the diagnosis of colon cancer. Finding the exact shape and size of polyps requires the segmentation of endoscopic images. This research explores the advantage of using depth-wise separable convolution in the atrous convolution of the ResUNet++ architecture. Deep atrous spatial pyramid pooling was also implemented on the ResUNet++ architecture. The results show that architecture with separable convolution has a smaller size and fewer GFLOPs without degrading the performance too much.
Deep Conditional Adversarial learning for polyp Segmentationmultimediaeval
Paper: http://ceur-ws.org/Vol-2882/paper22.pdf
Debapriya Banik and Debotosh Bhattacharjee : Deep Conditional Adversarial learning for polyp Segmentation. Proc. of MediaEval 2020, 14-15 December 2020, Online.
This approach has addressed the Medico automatic polyp segmentation challenge which is a part of Mediaeval 2020. We have proposed a deep conditional adversarial learning based network for the automatic polyp segmentation task. The network comprises of two interdependent models namely a generator and a discriminator. The generator network is a FCN employed for the prediction of the polyp mask while the discriminator enforces the segmentation to be as similar as the real segmented mask (ground truth). Our proposed model achieved a comparative result on the test dataset provided by the organizers of the challenge.
A Temporal-Spatial Attention Model for Medical Image Detectionmultimediaeval
Paper: http://ceur-ws.org/Vol-2882/paper21.pdf
Hwang Maxwell, Wu Cai, Hwang Kao-Shing, Xu Yong Si and Wu Chien-Hsing : A Temporal-Spatial Attention Model for Medical Image Detection. Proc. of MediaEval 2020, 14-15 December 2020, Online.
A local region model with attentive temporal-spatial pathways is proposed for automatically learning various target structures. The attentive spatial pathway highlights the salient region to generate bounding boxes and ignores irrelevant regions in an input image. The proposed attention mechanism allows efficient object localization and the overall predictive performance is increased because there are fewer false positives for the object detection task for medical images with manual annotations. The experimental results show that proposed models consistently increase the base architectures' predictive performance for different datasets and training sizes without undue computational efficiency.
HCMUS-Juniors 2020 at Medico Task in MediaEval 2020: Refined Deep Neural Netw...multimediaeval
Paper: http://ceur-ws.org/Vol-2882/paper20.pdf
YouTube: https://youtu.be/CVelQl5Luf0
Quoc-Huy Trinh, Minh-Van Nguyen, Thiet-Gia Huynh and Minh-Triet Tran : HCMUS-Juniors 2020 at Medico Task in MediaEval 2020: Refined Deep Neural Network and UNet for Polyps Segmentation. Proc. of MediaEval 2020, 14-15 December 2020, Online.
The Medico: Multimedia Task focuses on developing an efficient and accurate framework to computer-aided diagnosis systems for automatic polyp segmentation to detect all types of polyps in endoscopic images of the gastrointestinal (GI) tract. We are HCMUS-team approach a solution, which includes combination Residual module, Inception module, Adaptive Convolutional neural network with Unet model and PraNet to semantic segmentation all types of polyps in endoscopic images. We submit multiple runs with different architecture and parameters in our model. Our methods show potential results in accuracy and efficiency through multiple experiments.
Fine-tuning for Polyp Segmentation with Attentionmultimediaeval
Paper: http://ceur-ws.org/Vol-2882/paper15.pdf
Rabindra Khadka : Transfer of Knowledge: Fine-tuning for Polyp Segmentation with Attention. Proc. of MediaEval 2020, 14-15 December 2020, Online.
This paper describes how the transfer of prior knowledge can effectively take on segmentation tasks with the help of attention mechanisms. The UNet model pretrained on brain MRI dataset was fine-tuned with the polyp dataset. Attention mechanism was integrated to focus on relevant regions in the input images. The implemented architecture is evaluated on 200 validation images based on intersection over union and dice score between groundtruth and predicted region. The model demonstrates a promising result with computational efciency.
Bigger Networks are not Always Better: Deep Convolutional Neural Networks for...multimediaeval
Paper: http://ceur-ws.org/Vol-2882/paper12.pdf
Adrian Krenzer and Frank Puppe : Bigger Networks are not Always Better: Deep Convolutional Neural Networks for Automated Polyp Segmentation. Proc. of MediaEval 2020, 14-15 December 2020, Online.
This paper presents our team's (AI-JMU) approach to the Medico automated polyp segmentation challenge. We consider deep convolutional neural networks to be well suited for this task. To determine the best architecture we test and compare state of the art backbones and two different heads. Finally we achieve a Jaccard index of 73.74\% on the challenge test set. We further demonstrate that bigger networks do not always perform better. However the growing network size always increases the computational complexity.
Insights for wellbeing: Predicting Personal Air Quality Index using Regressio...multimediaeval
Paper: http://ceur-ws.org/Vol-2882/paper51.pdf
Amel Ksibi, Amina Salhi, Ala Alluhaidan and Sahar A. El-Rahman : Insights for wellbeing: Predicting Personal Air Quality Index using Regression Approach. Proc. of MediaEval 2020, 14-15 December 2020, Online.
Providing air pollution information to individuals enables them to understand the air quality of their living environments. Thus, the association between people’s wellbeing and the properties of the surrounding environment is an essential area of investigation. This paper proposes Air Quality Prediction through harvesting public/open data and leveraging them to get the Personal Air Quality index. These are usually incomplete. To cope with the problem of missing data, we applied the KNN imputation method. To predict Personal Air Quality Index, we apply a voting regression approach based on three base regressors which are Gradient Boosting regressor, Random Forest regressor, and linear regressor. Evaluating the experimental results using the RMSE metric, we got an average score of 35.39 for Walker and 51.16 for Car.
Use Visual Features From Surrounding Scenes to Improve Personal Air Quality ...multimediaeval
Paper: http://ceur-ws.org/Vol-2882/paper40.pdf
YouTube: https://youtu.be/SL5Hvu1mARY
Trung-Quan Nguyen, Dang-Hieu Nguyen and Loc Tai Tan Nguyen : Use Visual Features From Surrounding Scenes to Improve Personal Air Quality Data Prediction Performance. Proc. of MediaEval 2020, 14-15 December 2020, Online.
In this paper, we propose a method to predict the personal air quality index in an area by using the combination of the levels of the following pollutants: PM2.5, NO2, and O3, measured from the nearby weather stations of that area, and the photos of surrounding scenes taken at that area. Our approach uses the Inverse Distance Weighted (IDW) technique to estimate the missing air pollutant levels and then use regression to integrate visual features from taken photos to optimize the predicted values. After that, we can use those values to calculate the Air Quality Index (AQI). The results show that the proposed method may not improve the performance of the prediction in some cases.
Check out the webinar slides to learn more about how XfilesPro transforms Salesforce document management by leveraging its world-class applications. For more details, please connect with sales@xfilespro.com
If you want to watch the on-demand webinar, please click here: https://www.xfilespro.com/webinars/salesforce-document-management-2-0-smarter-faster-better/
Large Language Models and the End of ProgrammingMatt Welsh
Talk by Matt Welsh at Craft Conference 2024 on the impact that Large Language Models will have on the future of software development. In this talk, I discuss the ways in which LLMs will impact the software industry, from replacing human software developers with AI, to replacing conventional software with models that perform reasoning, computation, and problem-solving.
SOCRadar Research Team: Latest Activities of IntelBrokerSOCRadar
The European Union Agency for Law Enforcement Cooperation (Europol) has suffered an alleged data breach after a notorious threat actor claimed to have exfiltrated data from its systems. Infamous data leaker IntelBroker posted on the even more infamous BreachForums hacking forum, saying that Europol suffered a data breach this month.
The alleged breach affected Europol agencies CCSE, EC3, Europol Platform for Experts, Law Enforcement Forum, and SIRIUS. Infiltration of these entities can disrupt ongoing investigations and compromise sensitive intelligence shared among international law enforcement agencies.
However, this is neither the first nor the last activity of IntekBroker. We have compiled for you what happened in the last few days. To track such hacker activities on dark web sources like hacker forums, private Telegram channels, and other hidden platforms where cyber threats often originate, you can check SOCRadar’s Dark Web News.
Stay Informed on Threat Actors’ Activity on the Dark Web with SOCRadar!
top nidhi software solution freedownloadvrstrong314
This presentation emphasizes the importance of data security and legal compliance for Nidhi companies in India. It highlights how online Nidhi software solutions, like Vector Nidhi Software, offer advanced features tailored to these needs. Key aspects include encryption, access controls, and audit trails to ensure data security. The software complies with regulatory guidelines from the MCA and RBI and adheres to Nidhi Rules, 2014. With customizable, user-friendly interfaces and real-time features, these Nidhi software solutions enhance efficiency, support growth, and provide exceptional member services. The presentation concludes with contact information for further inquiries.
Globus Connect Server Deep Dive - GlobusWorld 2024Globus
We explore the Globus Connect Server (GCS) architecture and experiment with advanced configuration options and use cases. This content is targeted at system administrators who are familiar with GCS and currently operate—or are planning to operate—broader deployments at their institution.
Modern design is crucial in today's digital environment, and this is especially true for SharePoint intranets. The design of these digital hubs is critical to user engagement and productivity enhancement. They are the cornerstone of internal collaboration and interaction within enterprises.
Globus Compute wth IRI Workflows - GlobusWorld 2024Globus
As part of the DOE Integrated Research Infrastructure (IRI) program, NERSC at Lawrence Berkeley National Lab and ALCF at Argonne National Lab are working closely with General Atomics on accelerating the computing requirements of the DIII-D experiment. As part of the work the team is investigating ways to speedup the time to solution for many different parts of the DIII-D workflow including how they run jobs on HPC systems. One of these routes is looking at Globus Compute as a way to replace the current method for managing tasks and we describe a brief proof of concept showing how Globus Compute could help to schedule jobs and be a tool to connect compute at different facilities.
Why React Native as a Strategic Advantage for Startup Innovation.pdfayushiqss
Do you know that React Native is being increasingly adopted by startups as well as big companies in the mobile app development industry? Big names like Facebook, Instagram, and Pinterest have already integrated this robust open-source framework.
In fact, according to a report by Statista, the number of React Native developers has been steadily increasing over the years, reaching an estimated 1.9 million by the end of 2024. This means that the demand for this framework in the job market has been growing making it a valuable skill.
But what makes React Native so popular for mobile application development? It offers excellent cross-platform capabilities among other benefits. This way, with React Native, developers can write code once and run it on both iOS and Android devices thus saving time and resources leading to shorter development cycles hence faster time-to-market for your app.
Let’s take the example of a startup, which wanted to release their app on both iOS and Android at once. Through the use of React Native they managed to create an app and bring it into the market within a very short period. This helped them gain an advantage over their competitors because they had access to a large user base who were able to generate revenue quickly for them.
Your Digital Assistant.
Making complex approach simple. Straightforward process saves time. No more waiting to connect with people that matter to you. Safety first is not a cliché - Securely protect information in cloud storage to prevent any third party from accessing data.
Would you rather make your visitors feel burdened by making them wait? Or choose VizMan for a stress-free experience? VizMan is an automated visitor management system that works for any industries not limited to factories, societies, government institutes, and warehouses. A new age contactless way of logging information of visitors, employees, packages, and vehicles. VizMan is a digital logbook so it deters unnecessary use of paper or space since there is no requirement of bundles of registers that is left to collect dust in a corner of a room. Visitor’s essential details, helps in scheduling meetings for visitors and employees, and assists in supervising the attendance of the employees. With VizMan, visitors don’t need to wait for hours in long queues. VizMan handles visitors with the value they deserve because we know time is important to you.
Feasible Features
One Subscription, Four Modules – Admin, Employee, Receptionist, and Gatekeeper ensures confidentiality and prevents data from being manipulated
User Friendly – can be easily used on Android, iOS, and Web Interface
Multiple Accessibility – Log in through any device from any place at any time
One app for all industries – a Visitor Management System that works for any organisation.
Stress-free Sign-up
Visitor is registered and checked-in by the Receptionist
Host gets a notification, where they opt to Approve the meeting
Host notifies the Receptionist of the end of the meeting
Visitor is checked-out by the Receptionist
Host enters notes and remarks of the meeting
Customizable Components
Scheduling Meetings – Host can invite visitors for meetings and also approve, reject and reschedule meetings
Single/Bulk invites – Invitations can be sent individually to a visitor or collectively to many visitors
VIP Visitors – Additional security of data for VIP visitors to avoid misuse of information
Courier Management – Keeps a check on deliveries like commodities being delivered in and out of establishments
Alerts & Notifications – Get notified on SMS, email, and application
Parking Management – Manage availability of parking space
Individual log-in – Every user has their own log-in id
Visitor/Meeting Analytics – Evaluate notes and remarks of the meeting stored in the system
Visitor Management System is a secure and user friendly database manager that records, filters, tracks the visitors to your organization.
"Secure Your Premises with VizMan (VMS) – Get It Now"
Designing for Privacy in Amazon Web ServicesKrzysztofKkol1
Data privacy is one of the most critical issues that businesses face. This presentation shares insights on the principles and best practices for ensuring the resilience and security of your workload.
Drawing on a real-life project from the HR industry, the various challenges will be demonstrated: data protection, self-healing, business continuity, security, and transparency of data processing. This systematized approach allowed to create a secure AWS cloud infrastructure that not only met strict compliance rules but also exceeded the client's expectations.
Field Employee Tracking System| MiTrack App| Best Employee Tracking Solution|...informapgpstrackings
Keep tabs on your field staff effortlessly with Informap Technology Centre LLC. Real-time tracking, task assignment, and smart features for efficient management. Request a live demo today!
For more details, visit us : https://informapuae.com/field-staff-tracking/
Multiple Your Crypto Portfolio with the Innovative Features of Advanced Crypt...Hivelance Technology
Cryptocurrency trading bots are computer programs designed to automate buying, selling, and managing cryptocurrency transactions. These bots utilize advanced algorithms and machine learning techniques to analyze market data, identify trading opportunities, and execute trades on behalf of their users. By automating the decision-making process, crypto trading bots can react to market changes faster than human traders
Hivelance, a leading provider of cryptocurrency trading bot development services, stands out as the premier choice for crypto traders and developers. Hivelance boasts a team of seasoned cryptocurrency experts and software engineers who deeply understand the crypto market and the latest trends in automated trading, Hivelance leverages the latest technologies and tools in the industry, including advanced AI and machine learning algorithms, to create highly efficient and adaptable crypto trading bots
Software Engineering, Software Consulting, Tech Lead.
Spring Boot, Spring Cloud, Spring Core, Spring JDBC, Spring Security,
Spring Transaction, Spring MVC,
Log4j, REST/SOAP WEB-SERVICES.
First Steps with Globus Compute Multi-User EndpointsGlobus
In this presentation we will share our experiences around getting started with the Globus Compute multi-user endpoint. Working with the Pharmacology group at the University of Auckland, we have previously written an application using Globus Compute that can offload computationally expensive steps in the researcher's workflows, which they wish to manage from their familiar Windows environments, onto the NeSI (New Zealand eScience Infrastructure) cluster. Some of the challenges we have encountered were that each researcher had to set up and manage their own single-user globus compute endpoint and that the workloads had varying resource requirements (CPUs, memory and wall time) between different runs. We hope that the multi-user endpoint will help to address these challenges and share an update on our progress here.
We describe the deployment and use of Globus Compute for remote computation. This content is aimed at researchers who wish to compute on remote resources using a unified programming interface, as well as system administrators who will deploy and operate Globus Compute services on their research computing infrastructure.
Understanding Globus Data Transfers with NetSageGlobus
NetSage is an open privacy-aware network measurement, analysis, and visualization service designed to help end-users visualize and reason about large data transfers. NetSage traditionally has used a combination of passive measurements, including SNMP and flow data, as well as active measurements, mainly perfSONAR, to provide longitudinal network performance data visualization. It has been deployed by dozens of networks world wide, and is supported domestically by the Engagement and Performance Operations Center (EPOC), NSF #2328479. We have recently expanded the NetSage data sources to include logs for Globus data transfers, following the same privacy-preserving approach as for Flow data. Using the logs for the Texas Advanced Computing Center (TACC) as an example, this talk will walk through several different example use cases that NetSage can answer, including: Who is using Globus to share data with my institution, and what kind of performance are they able to achieve? How many transfers has Globus supported for us? Which sites are we sharing the most data with, and how is that changing over time? How is my site using Globus to move data internally, and what kind of performance do we see for those transfers? What percentage of data transfers at my institution used Globus, and how did the overall data transfer performance compare to the Globus users?
Gamify Your Mind; The Secret Sauce to Delivering Success, Continuously Improv...Shahin Sheidaei
Games are powerful teaching tools, fostering hands-on engagement and fun. But they require careful consideration to succeed. Join me to explore factors in running and selecting games, ensuring they serve as effective teaching tools. Learn to maintain focus on learning objectives while playing, and how to measure the ROI of gaming in education. Discover strategies for pitching gaming to leadership. This session offers insights, tips, and examples for coaches, team leads, and enterprise leaders seeking to teach from simple to complex concepts.
Advanced Flow Concepts Every Developer Should KnowPeter Caitens
Tim Combridge from Sensible Giraffe and Salesforce Ben presents some important tips that all developers should know when dealing with Flows in Salesforce.
Advanced Flow Concepts Every Developer Should Know
The NNI Query-by-Example System for MediaEval 2014
1. The NNI QbE-STD System for
MedialEval 2014
Peng Yang1, Haihua Xu2, Xiong Xiao2, Lei Xie1, Cheung-Chi Leung3
Hongjie Chen1, Jia Yu1, Hang Lv1, Lei Wang3, Su Jun Leow2
Bin Ma3, Eng Siong Chng1, Haizhou Li2,3
1Northwestern Polytechnical University, Xi’an, China
2Nanyang Technological University, Singapore
3Institute for Infocomm Research, A STAR, Singapore
Presented by Haihua Xu
Temasek Laboratories@NTU, Singapore
1
NNI QbE-STD system, MedialEval 2014 Workshop, Barcelona
2. System Diagram
Two groups of subsystems are used:
• Subsequence DTW-based template matching on Gaussian/phone posteriorgram
and bottleneck features.
• Symbolic search (SS) using phone tokenizer and weighted finite state transducer
(WFST)
NNI QbE-STD system, MedialEval 2014 Workshop, Barcelona
2
3. Tokenizers
Tokenizers are used to convert the audio signal into
• posteriorgram or bottleneck features for DTW based systems
• phone sequences/lattices for SS systems
3
NNI QbE-STD system, MedialEval 2014 Workshop, Barcelona
4. DTW-based Systems
• Full sequence matching1: conventional subsequence DTW. Good
for type 1 queries.
• Used partial matching for type 2&3 queries.
• Use partial feature segment of query for matching
• Segments are 600ms long and shifted by 50ms.
• Improved performance for Type 3 queries.
• 9 DTW systems
• 5 using full matching
• 4 using partial matching
1Yang P. et al, “Intrinsic spectral analysis based on temporal context features for query-by-example spoken term detection
”, in Proc. INTERSPEECH, 2014
4
NNI QbE-STD system, MedialEval 2014 Workshop, Barcelona
5. Why Symbolic Search (SS)
• DTW is effective1, but it is
• computationally expensive and difficult to be indexed,
• not easy to handle inexact match.
• Symbolic search allows indexing and fast search, e.g. using weighted
finite state transducer (WFST).
1Anguera X., Rodrigues-Fuentes L.J., Szoke I., Buzo A., and Metze F., “Query by example search on speech at mediaeval
2014”, in Working Notes Proceedings of the Mediaeval 2014 workshop, Barcelona, Spain, Oct. 16-17
5
NNI QbE-STD system, MedialEval 2014 Workshop, Barcelona
6. Symbolic Search System
6
NNI QbE-STD system, MedialEval 2014 Workshop, Barcelona
• Limitations of symbolic search for QbE-STD:
• Must use phone recognizers of other languages for
tokenization poor symbolic representation.
• Inconsistent phone representation between query
and search audio.
7. 7
NNI QbE-STD system, MedialEval 2014 Workshop, Barcelona
Limitation of Conventional Symbolic Search
• Full – Full symbolic search method
• pMiss – Miss rate
• pFA – False alarm rate
• ATWV – Actual Term Weighted Value
As query length increases,
• Missing rate approaches 100%
• False alarm rate approaches 0
• ATWV approaches 0
8. 8
NNI QbE-STD system, MedialEval 2014 Workshop, Barcelona
Partial Phone Sequence Matching
Partial Matching Steps
• If a query phone hypothesis is longer
than 6, get all partial sequences of the
hypothesis.
• Use all the unique partial sequences to
search.
• Search results are pooled and all
treated as the match of the query.
• Score normalization is applied, and
decision is made.
• High missing rate of long queries can be reduced by simply shorten the query
representation.
• Rationale: let the system return something first, and then decide which is true match.
9. 9
NNI QbE-STD system, MedialEval 2014 Workshop, Barcelona
Effectiveness of Partial Phone Sequence
Matching
Full – Full symbolic search method
Partial – Partial symbolic search method
pMiss – Miss rate
pFA – False alarm rate
ATWV – Actual Term Weighted Value
For queries longer than 6 phones:
• Missing rate reduced
• False alarm increased
• ATWV increased.
If beta is not 66.7, the best trade-
off point of pMiss and pFA will
change.
10. 10
Results
NNI QbE-STD system, MedialEval 2014 Workshop, Barcelona
• For type 1 query, the partial SS method is
obviously worse than DTW method.
• But for type 2 and 3 queries, the partial SS
method is comparable with DTW one.
• For type 3 query, the partial SS method is
significantly better than the DTW one in terms
MTWV.
• The two methods are very complementary.
11. Conclusion
11NNI QbE-STD system, MedialEval 2014 Workshop, Barcelona
We have described the NNI system for the QUESST 2014 Task
• DTW based subsystem
• Symbolic search subsystem
• Why conventional SS system is not working, especially for long queries
• Partial phone sequence SS method is proposed
• The NNI system results are reported
In future, research will be focused on reducing the false alarms introduced by the
partial matching method.