Como Llamarles?

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This Haiku Deck presentation contains 5 photos from different photographers to illustrate a topic. The presentation aims to inspire viewers to create their own Haiku Deck presentations on SlideShare. A call to action at the end encourages viewers to get started making their own presentations.

Photo by Rock City Kennels

Photo by Aris.Sanchez

Photo by Aris.Sanchez

Photo by Javier Delgado Esteban

Photo by Juanedc

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Presenter: Claire-Hélène Demarty MediaEval 2016 Predicting Media Interestingness Task In Working Notes Proceedings of the MediaEval 2016 Workshop, Hilversum, Netherlands, October 20-21, CEUR-WS.org (2016) by Claire-Hélène Demarty, Mats Sjöberg, Bogdan Ionescu, Thanh-Toan Do, Hanli Wang, Ngoc Q. K. Duong, and Frédéric Lefebvre Paper: http://ceur-ws.org/Vol-1739/MediaEval_2016_paper_1.pdf Video: https://youtu.be/rAarQaEr9-w Abstract: This paper provides an overview of the Predicting Media Interestingness task that is organized as part of the MediaEval 2016 Benchmarking Initiative for Multimedia Evaluation. The task, which is running for the first year, expects participants to create systems that automatically select images and video segments that are considered to be the most interesting for a common viewer. In this paper, we present the task use case and challenges, the proposed data set and ground truth, the required participant runs and the evaluation metrics.

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This paper details the participation of the UNED-UV group at the 2015 Retrieving Diverse Social Images Task. This year, our proposal is based on a multi-modal approach that firstly applies a textual algorithm based on Formal Concept Analysis (FCA) and Hierarchical Agglomerative Clustering (HAC) to detect the latent topics addressed by the images to diversify them according to these topics. Secondly, a Local Logistic Regression model, which uses the low level features and some relevant and non-relevant samples, is adjusted and estimates the relevance probability for all the images in the database. http://ceur-ws.org/Vol-1436/ http://www.multimediaeval.org

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Presenter: Miroslav Skácel BUT Zero-Cost Speech Recognition 2016 System Description In Working Notes Proceedings of the MediaEval 2016 Workshop, Hilversum, Netherlands, October 20-21, CEUR-WS.org (2016) by Miroslav Skácel, Martin Karafiát, Lucas Ondel, Albert Uchytil, Igor Szöke Paper: http://ceur-ws.org/Vol-1739/MediaEval_2016_paper_48.pdf Video: https://youtu.be/0pNiLLVTa28 Abstract: This paper describes our work on developing speech recognizers for Vietnamese. It focuses on procedures to prepare provided data precisely. We aim on analysis of the textual transcriptions in particular. Methods to filter out defective data to improve performance of final system are proposed and described in detail. We also propose cleaning of other textual data used for language modeling. Several architectures are investigated to reach both sub-tasks goals. The achieved results are discussed.

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Presenter: Samuel G. Fadel UNIFESP at MediaEval 2016: Predicting Media Interestingness Task In Working Notes Proceedings of the MediaEval 2016 Workshop, Hilversum, Netherlands, October 20-21, CEUR-WS.org (2016) by Jurandy Almeida Paper: http://ceur-ws.org/Vol-1739/MediaEval_2016_paper_28.pdf Video: https://youtu.be/YLthKNczlcA Abstract: This paper describes the approach proposed by UNIFESP for the MediaEval 2016 Predicting Media Interestingness Task and for its video subtask only. The proposed approach is based on combining learning-to-rank algorithms for predicting the interestingness of videos by their visual content.

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Como Llamarles?

1. Photo by Rock City Kennels

2. Photo by Aris.Sanchez

3. Photo by Aris.Sanchez

4. Photo by Javier Delgado Esteban

5. Photo by Juanedc

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