Ponències/Comunicacions de congressos
Enviaments recents
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LaViCAD: Laboratorio Virtual de Comunicaciones Analógicas y Digitales
(Universitat de Barcelona. Edicions i Publicacions, 2006)
Text en actes de congrés
Accés obertEn este trabajo se presenta tanto el diseño como la experimentación de un Laboratorio Virtual de Comunicaciones Analógicas y Digitales: LaViCAD. Mediante LaViCAD se pueden experimentar y verificar diferentes aplicaciones ... -
Online detection of action start in untrimmed, streaming videos
(Springer, 2018)
Comunicació de congrés
Accés restringit per política de l'editorialWe aim to tackle a novel task in action detection - Online Detection of Action Start (ODAS) in untrimmed, streaming videos. The goal of ODAS is to detect the start of an action instance, with high categorization accuracy ... -
Demonstration of an open source framework for qualitative evaluation of CBIR systems
(Association for Computing Machinery (ACM), 2018)
Comunicació de congrés
Accés obertEvaluating image retrieval systems in a quantitative way, for example by computing measures like mean average precision, allows for objective comparisons with a ground-truth. However, in cases where ground-truth is not ... -
Hybridnet for depth estimation and semantic segmentation
(Institute of Electrical and Electronics Engineers (IEEE), 2018)
Text en actes de congrés
Accés restringit per política de l'editorialSemantic segmentation and depth estimation are two important tasks in the area of image processing. Traditionally, these two tasks are addressed in an independent manner. However, for those applications where geometric and ... -
Oriented trajectories as a method for audience measurement
(2018)
Text en actes de congrés
Accés restringit per política de l'editorialThe quantification of the attention received by advertisements is of paramount importance to determine its effectiveness. In this work, a simple and effective objective method for the assessment of the attention given to ... -
Detection-aided liver lesion segmentation using deep learning
(2017)
Comunicació de congrés
Accés obertA fully automatic technique for segmenting the liver and localizing its unhealthy tissues is a convenient tool in order to diagnose hepatic diseases and assess the response to the according treatments. In this work we ... -
What is going on in the world? A display platform for media understanding
(Institute of Electrical and Electronics Engineers (IEEE), 2018)
Text en actes de congrés
Accés restringit per política de l'editorialNews broadcasters and on-line publishers daily generate a large amount of articles and videos describing events currently happening in the world. In this work, we present a system that automatically indexes videos from a ... -
3D point cloud segmentation using a fully connected conditional random field
(Institute of Electrical and Electronics Engineers (IEEE), 2017)
Comunicació de congrés
Accés restringit per política de l'editorialTraditional image segmentation methods working with low level image features are usually difficult to adapt to higher level tasks, such as object recognition and scene understanding. Object segmentation emerges as a new ... -
An interactive lifelog search engine for LSC2018
(Association for Computing Machinery (ACM), 2018)
Comunicació de congrés
Accés obertIn this work, we describe an interactive lifelog search engine developed for the LSC 2018 search challenge at ACM ICMR 2018. The paper introduces the four-step process required to support lifelog search engines and describes ... -
Masked V-Net: an approach to brain tumor segmentation
(2017)
Comunicació de congrés
Accés restringit per política de l'editorialThis paper introduces Masked V-Net architecture, a variant of the recently introduced V-Net[13] that reformulates the residual connections and uses a ROI mask to constrain the network to train only on relevant voxels. ... -
Comparing fixed and adaptive computation time for recurrent neural networks
(2018)
Text en actes de congrés
Accés obertDeep networks commonly perform better than shallow ones, but allocating the proper amount of computation for each particular input sample remains an open problem. This issue is particularly challenging in sequential tasks, ... -
Skip RNN: learning to skip state updates in recurrent neural networks
(2018)
Comunicació de congrés
Accés obertRecurrent Neural Networks (RNNs) continue to show outstanding performance in sequence modeling tasks. However, training RNNs on long sequences often face challenges like slow inference, vanishing gradients and difficulty ...
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