Co-advised Thesis in ETSETB mobility program

•

1 like•666 views

These slides present the proposals from the Image Processing Group at UPC for bachelor and master thesis in the framework of the mobility program of ETSETB - Telecom BCN. Contact the mentioned professors and check the ETSETB website for more details: https://www.etsetb.upc.edu/

Technology Entertainment & Humor

Co-advised thesis in
ETSETB mobility program
December 2013

Video Hyperlinking
Benoit Huet (EURECOM Sophia-Antipolis, France), Xavier Giró (UPC)

Video Hyperlinking
Benoit Huet (EURECOM Sophia-Antipolis, France), Xavier Giró (UPC)
When: Spring 14 (no Erasmus), Fall 14 or Spring 15
Target: MET
Contact: xavier.giro@upc.edu
●

●
●

Description
○ Suggest related videos after a search.
○ Multimedia analysis.
Goals
○ Submission to MediaEval 2014
Candidate Requirements
○ English

Retrieval of Videogames Recordings
Mathias Lux (Klagenfurt, Austria), Xavier Giró (UPC)

Retrieval of Videogames Recordings
Mathias Lux (Klagenfurt, Austria), Xavier Giró (UPC)
When: Spring 14 (no Erasmus), Fall 14 or Spring 15
Target: AV, CITTEL & MET
Contact: xavier.giro@upc.edu
●

●

●

Description
○ Transfer classic video retrieval techniques to
videos of games (eg. twitch.tv, hitbox.tv).
○ Multimedia analysis.
Goals
○ Build a retrieval system for video recordings
of games.
Candidate Requirements
○ Java & English

Crowdsourced Object Segmentation with a Game
Vincent Charvillat (Toulouse, France), Oge Marques (FAU, USA), Xavier Giró (UPC)

Crowdsourced Object Segmentation with a Game
Vincent Charvillat (Toulouse, France), Oge Marques (FAU, USA), Xavier Giró (UPC)
When: Spring 14 (no Erasmus), Fall 14 or Spring 15
Target: AV, CITTEL & MET
Contact: xavier.giro@upc.edu
●

●

●

Description
○ Humans in the object segmentation loop.
○ Gamification to capture user interaction.
Goals
○ Study on User Effort vs Segmentation Quality
○ Extension to video
○ Submission to CrowdMM 2014.
Candidate Requirements
○ Matlab & English

CPMC

EEG for Object Segementation in Natural Images
Eva Mohedano and Noel O’Connor (Dublin City University), Xavier Giró (UPC)

EEG for Object Segementation in Natural Images
Eva Mohedano and Noel O’Connor (Dublin City University), Xavier Giró (UPC)
When: Fall 2014
Target: AV, CITTEL & MET
Contact: xavier.giro@upc.edu
●

●
●

Description
○ Humans in the object segmentation loop.
○ EEGs to capture user interaction.
Goals
○ Study on User Effort vs Segmentation Quality
Candidate Requirements
○ Matlab & Good English

Super-resolution of images
Axel Kochale & Jordi Salvador (Technicolor Hannover, Germany), Javier Ruiz Hidalgo (UPC)

Super-resolution of images
Axel Kochale & Jordi Salvador (Technicolor Hannover, Germany), Javier Ruiz Hidalgo (UPC)
When: Spring 14 (no Erasmus), Fall 14
Target: AV & MET
Contact: j.ruiz@upc.edu
●

●

●

Description
○ Antialiasing robust upscaling
○ Super-resultion in multi-camera
enviroments
Goals
○ Build novel techniques to upscale
images
Candidate Requirements
○ C/C++, matlab & English

Inhouse proposals
●

Also some proposals in case you prefer not to leave...

Object Detection on Multiscale Image Segmentations
Xavier Giró (UPC)
●
When: Fall 2014, Spring 2015
Target: AV, CITTEL & MET
Contact: xavier.giro@upc.edu

●

●

Description
○ Bottom-up feature extraction.
○ Top-down selective search.
Goals
○ Assess the benefits of this approach in terms
of computation and accuracy.
Candidate Requirements
○ C/C++

Social Multimedia and Storytelling
Xavier Giró (UPC)
●
When: Fall 2014, Spring 2015
Target: AV, CITTEL & MET
Contact: xavier.giro@upc.edu

●

●

Description
○ Summarise a story with online content.
○ Multimedia analysis.
Goals
○ Capture and mix images from on social
networks.
○ Assess with MediaEval 2014 data
Candidate Requirements
○ Python/C++ & English

Final words
●

Presented requirements (dates,
programming skills, degrees…) are
orientative.

●

You have time to improve the required
skills before your departure.

●

Contact professor and/or apply if you feel
motivated by the topic.

Thank you !
Slides available on

and

.

https://imatge.upc.edu/web/people/xavier-giro
http://bitsearch.blogspot.com
https://twitter.com/DocXavi
https://www.facebook.com/ProfessorXavi
xavier.giro@upc.edu

Similar to Co-advised Thesis in ETSETB mobility program

MÜLLER and WAYSDORF Tracking and tracing circulation of audiovisual heritage ...

FIAT/IFTA

Yun-Tao Chen's work experiences in QNAP System Inc. from 2016 - 2021 Paper (Master Thesis): Automatically Count and Classify Multiple Colonies onMobile Device Captured Images https://ndltd.ncl.edu.tw/cgi-bin/gs32/gsweb.cgi/login?o=dnclcdr&s=id=%22104NTU05345038%22.&searchmode=basic Colony Counter App Demo Video: https://www.youtube.com/watch?v=B79vBqyc9eU Paper: Artificial intelligence-based decision-making for age-related macular degeneration https://pubmed.ncbi.nlm.nih.gov/30662564/ AI-CDSS: News https://epaper.ntuh.gov.tw/health/201908/special_3_1.html Press Conference (Video): https://youtu.be/Xt590fm29cM QuMagie: https://www.qnap.com/en/software/qumagie Koi Retail: https://www.qnap.com/zh-tw/software/koiretail https://www.facebook.com/watch/?v=475772333132794 2017 台灣人工智慧年會 https://www.youtube.com/watch?v=O9BM38n_a0g

Yun-Tao Chen Resume 2021

Yun-tao Chen

The aim of the Advanced Master is to provide students with a cross-disciplinary culture of computational design, from parametric conception to extensive knowledge of the impact of digital design and making tools on artistic professions, design, urban planning, architecture and engineering. The training has been designed as an augmented experience including courses, prototyping workshops, conferences, maker-spaces visits and networking events. The courses and conferences will take place in multiple locations in Paris, making this training a true opportunity to discover innovative places in the capital.

Advanced Master in Computational Design & Making

Design By Data

A FUNUMENTARY: Take what you can, give nothing back... (NOT)

Open Knowledge Belgium

Severino Alfonso Dunn _ CV

Severino Alfonso Dunn

Video Analysis in Autonomous Systems: Data Analytics Challenges

krishna_dubba

ECCV2022 paper reading - MultiMAE: Multi-modal Multi-task Masked Autoencoders...

Antonio Tejero de Pablos

EMPOWER Artificial Intelligence webinar week: by Jesus Boticario

EADTU

Les danses extatiques andres busrbano.pptx (3)

Alexandra Sierra

This presentation will provide an overview of the recent activities carried out on quality assessment of immersive media within the Video Quality Experts Group (VQEG), particularly within the Immersive Media Group (IMG). Among other efforts, outcomes will be presented from the cross-lab test (carried out by ten different labs) in order to assess and validate subjective evaluation methodologies for 360º videos, which was instrumental in the development of the ITU-T Recommendation P.919. Also, insights will be provided on the current plans on exploring the evaluation of the quality of experience of immersive communication systems, considering different technologies such as 360º video, point cloud, free-viewpoint video, etc.

Quality assessment of immersive media: Recent activities within VQEG

Alpen-Adria-Universität

Similar to Co-advised Thesis in ETSETB mobility program (10)

MÜLLER and WAYSDORF Tracking and tracing circulation of audiovisual heritage ...

Yun-Tao Chen Resume 2021

Advanced Master in Computational Design & Making

A FUNUMENTARY: Take what you can, give nothing back... (NOT)

Severino Alfonso Dunn _ CV

Video Analysis in Autonomous Systems: Data Analytics Challenges

ECCV2022 paper reading - MultiMAE: Multi-modal Multi-task Masked Autoencoders...

EMPOWER Artificial Intelligence webinar week: by Jesus Boticario

Les danses extatiques andres busrbano.pptx (3)

Quality assessment of immersive media: Recent activities within VQEG

More from Universitat Politècnica de Catalunya

This document provides an overview of deep generative learning and summarizes several key generative models including GANs, VAEs, diffusion models, and autoregressive models. It discusses the motivation for generative models and their applications such as image generation, text-to-image synthesis, and enhancing other media like video and speech. Example state-of-the-art models are provided for each application. The document also covers important concepts like the difference between discriminative and generative modeling, sampling techniques, and the training procedures for GANs and VAEs.

Deep Generative Learning for All - The Gen AI Hype (Spring 2024)

Universitat Politècnica de Catalunya

Deep Generative Learning for All

Universitat Politècnica de Catalunya

The Transformer in Vision | Xavier Giro | Master in Computer Vision Barcelona...

Universitat Politècnica de Catalunya

Machine translation and computer vision have greatly benefited from the advances in deep learning. A large and diverse amount of textual and visual data have been used to train neural networks whether in a supervised or self-supervised manner. Nevertheless, the convergence of the two fields in sign language translation and production still poses multiple open challenges, like the low video resources, limitations in hand pose estimation, or 3D spatial grounding from poses.

Towards Sign Language Translation & Production | Xavier Giro-i-Nieto

Universitat Politècnica de Catalunya

The Transformer - Xavier Giró - UPC Barcelona 2021

Universitat Politècnica de Catalunya

Learning Representations for Sign Language Videos - Xavier Giro - NIST TRECVI...

Universitat Politècnica de Catalunya

Machine translation and computer vision have greatly benefited of the advances in deep learning. The large and diverse amount of textual and visual data have been used to train neural networks whether in a supervised or self-supervised manner. Nevertheless, the convergence of the two field in sign language translation and production is still poses multiple open challenges, like the low video resources, limitations in hand pose estimation, or 3D spatial grounding from poses. This talk will present these challenges and the How2✌️Sign dataset (https://how2sign.github.io) recorded at CMU in collaboration with UPC, BSC, Gallaudet University and Facebook. https://imatge.upc.edu/web/publications/sign-language-translation-and-production-multimedia-and-multimodal-challenges-all

Open challenges in sign language translation and production

Universitat Politècnica de Catalunya

https://imatge-upc.github.io/synthref/ Integrating computer vision with natural language processing has achieved significant progress over the last years owing to the continuous evolution of deep learning. A novel vision and language task, which is tackled in the present Master thesis is referring video object segmentation, in which a language query defines which instance to segment from a video sequence. One of the biggest challenges for this task is the lack of relatively large annotated datasets since a tremendous amount of time and human effort is required for annotation. Moreover, existing datasets suffer from poor quality annotations in the sense that approximately one out of ten language expressions fails to uniquely describe the target object. The purpose of the present Master thesis is to address these challenges by proposing a novel method for generating synthetic referring expressions for an image (video frame). This method pro- duces synthetic referring expressions by using only the ground-truth annotations of the objects as well as their attributes, which are detected by a state-of-the-art object detection deep neural network. One of the advantages of the proposed method is that its formulation allows its application to any object detection or segmentation dataset. By using the proposed method, the first large-scale dataset with synthetic referring expressions for video object segmentation is created, based on an existing large benchmark dataset for video instance segmentation. A statistical analysis and comparison of the created synthetic dataset with existing ones is also provided in the present Master thesis. The conducted experiments on three different datasets used for referring video object segmentation prove the efficiency of the generated synthetic data. More specifically, the obtained results demonstrate that by pre-training a deep neural network with the proposed synthetic dataset one can improve the ability of the network to generalize across different datasets, without any additional annotation cost. This outcome is even more important taking into account that no additional annotation cost is involved.

Generation of Synthetic Referring Expressions for Object Segmentation in Videos

Universitat Politècnica de Catalunya

Master MATT thesis defense by Juan José Nieto Advised by Víctor Campos and Xavier Giro-i-Nieto. 27th May 2021. Pre-training Reinforcement Learning (RL) agents in a task-agnostic manner has shown promising results. However, previous works still struggle to learn and discover meaningful skills in high-dimensional state-spaces. We approach the problem by leveraging unsupervised skill discovery and self-supervised learning of state representations. In our work, we learn a compact latent representation by making use of variational or contrastive techniques. We demonstrate that both allow learning a set of basic navigation skills by maximizing an information theoretic objective. We assess our method in Minecraft 3D maps with different complexities. Our results show that representations and conditioned policies learned from pixels are enough for toy examples, but do not scale to realistic and complex maps. We also explore alternative rewards and input observations to overcome these limitations. https://imatge.upc.edu/web/publications/discovery-and-learning-navigation-goals-pixels-minecraft

Discovery and Learning of Navigation Goals from Pixels in Minecraft

Universitat Politècnica de Catalunya

Peter Muschick MSc thesis Universitat Pollitecnica de Catalunya, 2020 Sign language recognition and translation has been an active research field in the recent years with most approaches using deep neural networks to extract information from sign language data. This work investigates the mostly disregarded approach of using human keypoint estimation from image and video data with OpenPose in combination with transformer network architecture. Firstly, it was shown that it is possible to recognize individual signs (4.5% word error rate (WER)). Continuous sign language recognition though was more error prone (77.3% WER) and sign language translation was not possible using the proposed methods, which might be due to low accuracy scores of human keypoint estimation by OpenPose and accompanying loss of information or insufficient capacities of the used transformer model. Results may improve with the use of datasets containing higher repetition rates of individual signs or focusing more precisely on keypoint extraction of hands.

Learn2Sign : Sign language recognition and translation using human keypoint e...

Universitat Politècnica de Catalunya

Intepretability / Explainable AI for Deep Neural Networks

Universitat Politècnica de Catalunya

Deep learning technologies are at the core of the current revolution in artificial intelligence for multimedia data analysis. The convergence of large-scale annotated datasets and affordable GPU hardware has allowed the training of neural networks for data analysis tasks which were previously addressed with hand-crafted features. Architectures such as convolutional neural networks, recurrent neural networks or Q-nets for reinforcement learning have shaped a brand new scenario in signal processing. This course will cover the basic principles of deep learning from both an algorithmic and computational perspectives.

Convolutional Neural Networks - Xavier Giro - UPC TelecomBCN Barcelona 2020

Universitat Politècnica de Catalunya

Self-Supervised Audio-Visual Learning - Xavier Giro - UPC TelecomBCN Barcelon...

Universitat Politècnica de Catalunya

Attention for Deep Learning - Xavier Giro - UPC TelecomBCN Barcelona 2020

Universitat Politècnica de Catalunya

https://telecombcn-dl.github.io/dlai-2020/ Deep learning technologies are at the core of the current revolution in artificial intelligence for multimedia data analysis. The convergence of large-scale annotated datasets and affordable GPU hardware has allowed the training of neural networks for data analysis tasks which were previously addressed with hand-crafted features. Architectures such as convolutional neural networks, recurrent neural networks or Q-nets for reinforcement learning have shaped a brand new scenario in signal processing. This course will cover the basic principles of deep learning from both an algorithmic and computational perspectives.

Generative Adversarial Networks GAN - Xavier Giro - UPC TelecomBCN Barcelona ...

Universitat Politècnica de Catalunya

https://telecombcn-dl.github.io/drl-2020/ This course presents the principles of reinforcement learning as an artificial intelligence tool based on the interaction of the machine with its environment, with applications to control tasks (eg. robotics, autonomous driving) o decision making (eg. resource optimization in wireless communication networks). It also advances in the development of deep neural networks trained with little or no supervision, both for discriminative and generative tasks, with special attention on multimedia applications (vision, language and speech).

Q-Learning with a Neural Network - Xavier Giró - UPC Barcelona 2020

Universitat Politècnica de Catalunya

Giro-i-Nieto, X. One Perceptron to Rule Them All: Language, Vision, Audio and Speech. In Proceedings of the 2020 International Conference on Multimedia Retrieval (pp. 7-8). Tutorial page: https://imatge.upc.edu/web/publications/one-perceptron-rule-them-all-language-vision-audio-and-speech-tutorial Deep neural networks have boosted the convergence of multimedia data analytics in a unified framework shared by practitioners in natural language, vision and speech. Image captioning, lip reading or video sonorization are some of the first applications of a new and exciting field of research exploiting the generalization properties of deep neural representation. This tutorial will firstly review the basic neural architectures to encode and decode vision, text and audio, to later review the those models that have successfully translated information across modalities.

Language and Vision with Deep Learning - Xavier Giró - ACM ICMR 2020 (Tutorial)

Universitat Politècnica de Catalunya

Image segmentation is a classic computer vision task that aims at labeling pixels with semantic classes. These slides provide an overview of the basic approaches applied from the deep learning field to tackle this challenge and presents the basic subtasks (semantic, instance and panoptic segmentation) and related datasets. Presented at the International Summer School on Deep Learning (ISSonDL) 2020 held online and organized by the University of Gdansk (Poland) between the 30th August and 2nd September. http://2020.dl-lab.eu/virtual-summer-school-on-deep-learning/

Image Segmentation with Deep Learning - Xavier Giro & Carles Ventura - ISSonD...

Universitat Politècnica de Catalunya

https://imatge-upc.github.io/rvos-mots/ Video object segmentation can be understood as a sequence-to-sequence task that can benefit from the curriculum learning strategies for better and faster training of deep neural networks. This work explores different schedule sampling and frame skipping variations to significantly improve the performance of a recurrent architecture. Our results on the car class of the KITTI-MOTS challenge indicate that, surprisingly, an inverse schedule sampling is a better option than a classic forward one. Also, that a progressive skipping of frames during training is beneficial, but only when training with the ground truth masks instead of the predicted ones.

Curriculum Learning for Recurrent Video Object Segmentation

Universitat Politècnica de Catalunya

Deep neural networks have achieved outstanding results in various applications such as vision, language, audio, speech, or reinforcement learning. These powerful function approximators typically require large amounts of data to be trained, which poses a challenge in the usual case where little labeled data is available. During the last year, multiple solutions have been proposed to leverage this problem, based on the concept of self-supervised learning, which can be understood as a specific case of unsupervised learning. This talk will cover its basic principles and provide examples in the field of multimedia.

Deep Self-supervised Learning for All - Xavier Giro - X-Europe 2020

Universitat Politècnica de Catalunya

More from Universitat Politècnica de Catalunya (20)

Deep Generative Learning for All - The Gen AI Hype (Spring 2024)

Deep Generative Learning for All

The Transformer in Vision | Xavier Giro | Master in Computer Vision Barcelona...

Towards Sign Language Translation & Production | Xavier Giro-i-Nieto

The Transformer - Xavier Giró - UPC Barcelona 2021

Learning Representations for Sign Language Videos - Xavier Giro - NIST TRECVI...

Open challenges in sign language translation and production

Generation of Synthetic Referring Expressions for Object Segmentation in Videos

Discovery and Learning of Navigation Goals from Pixels in Minecraft

Learn2Sign : Sign language recognition and translation using human keypoint e...

Intepretability / Explainable AI for Deep Neural Networks

Convolutional Neural Networks - Xavier Giro - UPC TelecomBCN Barcelona 2020

Self-Supervised Audio-Visual Learning - Xavier Giro - UPC TelecomBCN Barcelon...

Attention for Deep Learning - Xavier Giro - UPC TelecomBCN Barcelona 2020

Generative Adversarial Networks GAN - Xavier Giro - UPC TelecomBCN Barcelona ...

Q-Learning with a Neural Network - Xavier Giró - UPC Barcelona 2020

Language and Vision with Deep Learning - Xavier Giró - ACM ICMR 2020 (Tutorial)

Image Segmentation with Deep Learning - Xavier Giro & Carles Ventura - ISSonD...

Curriculum Learning for Recurrent Video Object Segmentation

Deep Self-supervised Learning for All - Xavier Giro - X-Europe 2020

Recently uploaded

This presentations targets students or working professionals. You may know Google for search, YouTube, Android, Chrome, and Gmail, but did you know Google has many developer tools, platforms & APIs? This comprehensive yet still high-level overview outlines the most impactful tools for where to run your code, store & analyze your data. It will also inspire you as to what's possible. This talk is 50 minutes in length.

Powerful Google developer tools for immediate impact! (2023-24 C)

wesley chun

ProductAnonymous-April2024-WinProductDiscovery-MelissaKlemke

Product Anonymous

Discord is a free app offering voice, video, and text chat functionalities, primarily catering to the gaming community. It serves as a hub for users to create and join servers tailored to their interests. Discord’s ecosystem comprises servers, each functioning as a distinct online community with its own channels dedicated to specific topics or activities. Users can engage in text-based discussions, voice calls, or video chats within these channels. Understanding Discord Servers Discord servers are virtual spaces where users congregate to interact, share content, and build communities. Servers may revolve around gaming, hobbies, interests, or fandoms, providing a platform for like-minded individuals to connect. Communication Features Discord offers a range of communication tools, including text channels for messaging, voice channels for real-time audio conversations, and video channels for face-to-face interactions. These features facilitate seamless communication and collaboration. What Does NSFW Mean? The acronym NSFW stands for “Not Safe For Work,” indicating content that may be inappropriate for professional or public settings. NSFW Content NSFW content encompasses material that is sexually explicit, violent, or otherwise graphic in nature. It often includes nudity, profanity, or depictions of sensitive topics.

Understanding Discord NSFW Servers A Guide for Responsible Users.pdf

UK Journal

Abhishek Deb(1), Mr Abdul Kalam(2) M. Des (UX) , School of Design, DIT University , Dehradun. This paper explores the future potential of AI-enabled smartphone processors, aiming to investigate the advancements, capabilities, and implications of integrating artificial intelligence (AI) into smartphone technology. The research study goals consist of evaluating the development of AI in mobile phone processors, analyzing the existing state as well as abilities of AI-enabled cpus determining future patterns as well as chances together with reviewing obstacles as well as factors to consider for more growth.

Exploring the Future Potential of AI-Enabled Smartphone Processors

debabhi2

With more memory available, system performance of three Dell devices increased, which can translate to a better user experience Conclusion When your system has plenty of RAM to meet your needs, you can efficiently access the applications and data you need to finish projects and to-do lists without sacrificing time and focus. Our test results show that with more memory available, three Dell PCs delivered better performance and took less time to complete the Procyon Office Productivity benchmark. These advantages translate to users being able to complete workflows more quickly and multitask more easily. Whether you need the mobility of the Latitude 5440, the creative capabilities of the Precision 3470, or the high performance of the OptiPlex Tower Plus 7010, configuring your system with more RAM can help keep processes running smoothly, enabling you to do more without compromising performance.

Boost PC performance: How more available memory can improve productivity

Principled Technologies

Developing An App To Navigate The Roads of Brazil

V3cube

Effective data discovery is crucial for maintaining compliance and mitigating risks in today's rapidly evolving privacy landscape. However, traditional manual approaches often struggle to keep pace with the growing volume and complexity of data. Join us for an insightful webinar where industry leaders from TrustArc and Privya will share their expertise on leveraging AI-powered solutions to revolutionize data discovery. You'll learn how to: - Effortlessly maintain a comprehensive, up-to-date data inventory - Harness code scanning insights to gain complete visibility into data flows leveraging the advantages of code scanning over DB scanning - Simplify compliance by leveraging Privya's integration with TrustArc - Implement proven strategies to mitigate third-party risks Our panel of experts will discuss real-world case studies and share practical strategies for overcoming common data discovery challenges. They'll also explore the latest trends and innovations in AI-driven data management, and how these technologies can help organizations stay ahead of the curve in an ever-changing privacy landscape.

TrustArc Webinar - Unlock the Power of AI-Driven Data Discovery

TrustArc

GenAI Risks & Security Meetup 01052024.pdf

lior mazor

The 7 Things I Know About Cyber Security After 25 Years | April 2024

Rafal Los

Finology Group – Insurtech Innovation Award 2024

The Digital Insurer

Real Time Object Detection Using Open CV

Khem

Workshop - Best of Both Worlds_ Combine KG and Vector search for enhanced R...

Neo4j

Data Cloud, More than a CDP by Matt Robison

Anna Loughnan Colquhoun

[2024]Digital Global Overview Report 2024 Meltwater.pdf

hans926745

How to Troubleshoot Apps for the Modern Connected Worker

ThousandEyes

How to Troubleshoot Apps for the Modern Connected Worker

ThousandEyes

The value of a flexible API Management solution for Open Banking Steve Melan, Manager for IT Innovation and Architecture - State's and Saving's Bank of Luxembourg Apidays New York 2024: The API Economy in the AI Era (April 30 & May 1, 2024) ------ Check out our conferences at https://www.apidays.global/ Do you want to sponsor or talk at one of our conferences? https://apidays.typeform.com/to/ILJeAaV8 Learn more on APIscene, the global media made by the community for the community: https://www.apiscene.io Explore the API ecosystem with the API Landscape: https://apilandscape.apiscene.io/

Apidays New York 2024 - The value of a flexible API Management solution for O...

apidays

presentation ICT roal in 21st century education

jfdjdjcjdnsjd

Enterprise Knowledge’s Urmi Majumder, Principal Data Architecture Consultant, and Fernando Aguilar Islas, Senior Data Science Consultant, presented "Driving Behavioral Change for Information Management through Data-Driven Green Strategy" on March 27, 2024 at Enterprise Data World (EDW) in Orlando, Florida. In this presentation, Urmi and Fernando discussed a case study describing how the information management division in a large supply chain organization drove user behavior change through awareness of the carbon footprint of their duplicated and near-duplicated content, identified via advanced data analytics. Check out their presentation to gain valuable perspectives on utilizing data-driven strategies to influence positive behavioral shifts and support sustainability initiatives within your organization. In this session, participants gained answers to the following questions: - What is a Green Information Management (IM) Strategy, and why should you have one? - How can Artificial Intelligence (AI) and Machine Learning (ML) support your Green IM Strategy through content deduplication? - How can an organization use insights into their data to influence employee behavior for IM? - How can you reap additional benefits from content reduction that go beyond Green IM?

Driving Behavioral Change for Information Management through Data-Driven Gree...

Enterprise Knowledge

Histor y of HAM Radio presentation slide

vu2urc

Recently uploaded (20)

Powerful Google developer tools for immediate impact! (2023-24 C)

ProductAnonymous-April2024-WinProductDiscovery-MelissaKlemke

Understanding Discord NSFW Servers A Guide for Responsible Users.pdf

Exploring the Future Potential of AI-Enabled Smartphone Processors

Boost PC performance: How more available memory can improve productivity

Developing An App To Navigate The Roads of Brazil

TrustArc Webinar - Unlock the Power of AI-Driven Data Discovery

GenAI Risks & Security Meetup 01052024.pdf

The 7 Things I Know About Cyber Security After 25 Years | April 2024

Finology Group – Insurtech Innovation Award 2024

Real Time Object Detection Using Open CV

Workshop - Best of Both Worlds_ Combine KG and Vector search for enhanced R...

Data Cloud, More than a CDP by Matt Robison

[2024]Digital Global Overview Report 2024 Meltwater.pdf

How to Troubleshoot Apps for the Modern Connected Worker

Apidays New York 2024 - The value of a flexible API Management solution for O...

presentation ICT roal in 21st century education

Driving Behavioral Change for Information Management through Data-Driven Gree...

Histor y of HAM Radio presentation slide

Co-advised Thesis in ETSETB mobility program

1. Co-advised thesis in ETSETB mobility program December 2013

2. Classic thesis

3. Classic thesis + mobility ?

4. Co-advised thesis + mobility

5. Co-advised thesis

6. Video Hyperlinking Benoit Huet (EURECOM Sophia-Antipolis, France), Xavier Giró (UPC)

7. Video Hyperlinking Benoit Huet (EURECOM Sophia-Antipolis, France), Xavier Giró (UPC) When: Spring 14 (no Erasmus), Fall 14 or Spring 15 Target: MET Contact: xavier.giro@upc.edu ● ● ● Description ○ Suggest related videos after a search. ○ Multimedia analysis. Goals ○ Submission to MediaEval 2014 Candidate Requirements ○ English

8. Retrieval of Videogames Recordings Mathias Lux (Klagenfurt, Austria), Xavier Giró (UPC)

9. Retrieval of Videogames Recordings Mathias Lux (Klagenfurt, Austria), Xavier Giró (UPC) When: Spring 14 (no Erasmus), Fall 14 or Spring 15 Target: AV, CITTEL & MET Contact: xavier.giro@upc.edu ● ● ● Description ○ Transfer classic video retrieval techniques to videos of games (eg. twitch.tv, hitbox.tv). ○ Multimedia analysis. Goals ○ Build a retrieval system for video recordings of games. Candidate Requirements ○ Java & English

10. Crowdsourced Object Segmentation with a Game Vincent Charvillat (Toulouse, France), Oge Marques (FAU, USA), Xavier Giró (UPC)

11. Crowdsourced Object Segmentation with a Game Vincent Charvillat (Toulouse, France), Oge Marques (FAU, USA), Xavier Giró (UPC) When: Spring 14 (no Erasmus), Fall 14 or Spring 15 Target: AV, CITTEL & MET Contact: xavier.giro@upc.edu ● ● ● Description ○ Humans in the object segmentation loop. ○ Gamification to capture user interaction. Goals ○ Study on User Effort vs Segmentation Quality ○ Extension to video ○ Submission to CrowdMM 2014. Candidate Requirements ○ Matlab & English CPMC

12. EEG for Object Segementation in Natural Images Eva Mohedano and Noel O’Connor (Dublin City University), Xavier Giró (UPC)

13. EEG for Object Segementation in Natural Images Eva Mohedano and Noel O’Connor (Dublin City University), Xavier Giró (UPC) When: Fall 2014 Target: AV, CITTEL & MET Contact: xavier.giro@upc.edu ● ● ● Description ○ Humans in the object segmentation loop. ○ EEGs to capture user interaction. Goals ○ Study on User Effort vs Segmentation Quality Candidate Requirements ○ Matlab & Good English

14. Super-resolution of images Axel Kochale & Jordi Salvador (Technicolor Hannover, Germany), Javier Ruiz Hidalgo (UPC)

15. Super-resolution of images Axel Kochale & Jordi Salvador (Technicolor Hannover, Germany), Javier Ruiz Hidalgo (UPC) When: Spring 14 (no Erasmus), Fall 14 Target: AV & MET Contact: j.ruiz@upc.edu ● ● ● Description ○ Antialiasing robust upscaling ○ Super-resultion in multi-camera enviroments Goals ○ Build novel techniques to upscale images Candidate Requirements ○ C/C++, matlab & English

16. Inhouse proposals ● Also some proposals in case you prefer not to leave...

17. Object Detection on Multiscale Image Segmentations Xavier Giró (UPC) ● When: Fall 2014, Spring 2015 Target: AV, CITTEL & MET Contact: xavier.giro@upc.edu ● ● Description ○ Bottom-up feature extraction. ○ Top-down selective search. Goals ○ Assess the benefits of this approach in terms of computation and accuracy. Candidate Requirements ○ C/C++

18. Social Multimedia and Storytelling Xavier Giró (UPC) ● When: Fall 2014, Spring 2015 Target: AV, CITTEL & MET Contact: xavier.giro@upc.edu ● ● Description ○ Summarise a story with online content. ○ Multimedia analysis. Goals ○ Capture and mix images from on social networks. ○ Assess with MediaEval 2014 data Candidate Requirements ○ Python/C++ & English

19. Final words ● Presented requirements (dates, programming skills, degrees…) are orientative. ● You have time to improve the required skills before your departure. ● Contact professor and/or apply if you feel motivated by the topic.

20. Thank you ! Slides available on and . https://imatge.upc.edu/web/people/xavier-giro http://bitsearch.blogspot.com https://twitter.com/DocXavi https://www.facebook.com/ProfessorXavi xavier.giro@upc.edu

Co-advised Thesis in ETSETB mobility program

Recommended

Recommended

More Related Content

Similar to Co-advised Thesis in ETSETB mobility program

Similar to Co-advised Thesis in ETSETB mobility program (10)

More from Universitat Politècnica de Catalunya

More from Universitat Politècnica de Catalunya (20)

Recently uploaded

Recently uploaded (20)

Co-advised Thesis in ETSETB mobility program