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Canton-Ferrer C, Canton-Ferrer C, Casas J, Pardàs M, Sargin M, Tekalp M. 3D Human Action Recognition In Multiple View Scenarios. In 2ones Jornades UPC de Investigación en Automática, Visión y Robótica. 2006. pp. 1–5.
Canton-Ferrer C, Casas J, Pardàs M. Marker-based human motion capture in multi-view sequences. Eurasip journal on advances in signal processing. 2010;2010:1–11.
Cànaves MArtigues. Prevention of Alzheimer's Disease: a contribution from MRI and machine learning. Petrone P, Vilaplana V. 2018.
Campos V, Jou B, Giró-i-Nieto X. From Pixels to Sentiment: Fine-tuning CNNs for Visual Sentiment Prediction. Image and Vision Computing. 2017;.  (1.92 MB)
Campos V, Giró-i-Nieto X, Jou B, Torres J, Chang S-F. Sentiment concept embedding for visual affect recognition. In Multimodal Behavior Analysis in theWild. 1st ed. Elsevier; 2018.
Campos V. Learning to Skip State Updates in Recurrent Neural Networks. Jou B, Chang S-F, Giró-i-Nieto X. 2017.  (961.49 KB)
Campos V, Jou B, Giró-i-Nieto X, Torres J, Chang S-F. Skip RNN: Learning to Skip State Updates in Recurrent Neural Networks. In International Conference on Learning Representations (ICLR). 2018.
Campos V, Giró-i-Nieto X, Torres J. Importance Weighted Evolution Strategies. In NeurIPS 2018 Deep Reinforcement Learning Workshop . Montreal, Quebec; 2018.  (362.25 KB)
Campos V, Trott A, Xiong C, Socher R, Giró-i-Nieto X, Torres J. Explore, Discover and Learn: Unsupervised Discovery of State-Covering Skills. In International Conference on Machine Learning (ICML) 2020. 2020.  (6.89 MB)
Campos V, Salvador A, Giró-i-Nieto X, Jou B. Diving Deep into Sentiment: Understanding Fine-tuned CNNs for Visual Sentiment Prediction. In 1st International Workshop on Affect and Sentiment in Multimedia. Brisbane, Australia: ACM; 2015.  (506.22 KB)
Campos V. Deep Learning that Scales: Leveraging Compute and Data. Torres J, Giró-i-Nieto X. Computer Architecture. [Barcelona, Catalonia]: Universitat Politècnica de Catalunya; 2020.  (8.55 MB)
Campos V. Layer-wise CNN Surgery for Visual Sentiment Prediction. Salvador A, Jou B, Giró-i-Nieto X. 2015.  (1.51 MB)
Campos V, Jou B, Giró-i-Nieto X, Torres J, Chang S-F. Skip RNN: Learning to Skip State Updates in Recurrent Neural Networks. In NIPS Time Series Workshop 2017. Long Beach, CA, USA; 2017.  (427.72 KB)
Campos V, Sastre F, Yagües M, Bellver M, Giró-i-Nieto X, Torres J. Distributed training strategies for a computer vision deep learning algorithm on a distributed GPU cluster. In International Conference on Computational Science (ICCS). Zurich, Switzerland: Elsevier; 2017.  (576.67 KB)
Caminal I, Casas J, Royo S. SLAM-based 3D outdoor reconstructions from LIDAR data. In IC3D. Brussels, Belgium: IEEE; 2018.  (3.21 MB)
Calderero F. Information Theoretical Region Merging Approaches and Fusion of Hierarchical Image Segmentation Results. Marqués F. Universitat Politècnica de Catalunya (UPC); 2010.  (57.57 MB)
Calderero F, Marqués F. General Region Merging Based on First Order Markov Information Theory Statistical Measures. In 16th European Signal Processing Conference. 2008.
Calderero F, Marqués F, Ortega A. Multiple view region matching using as a Lagrangian optimization problem. In 2007 International Conference on Acoustics, Speech and Signal Processing. 2007.
Calderero F, Marqués F. Hierarchical fusion of color and depth information at partition level by cooperative region merging. In IEEE International Conference on Acoustics, Speech and Signal Processing 2009. 2009. pp. 973–976.
Calderero F, Marqués F, Ortega A. Performance evaluation of probability density estimators for unsupervised information theoretical region merging. In 16th International Conference on Image Processing. 2009. pp. 4397–4400.
Calderero F, Marqués F. Image Analysis and Understanding Based on Information Theoretical Region Merging Approaches for Segmentation and Cooperative Fusion. In Handbook of Research on Computational Intelligence for Engineering, Science, and Business. IGI Global; 2012. pp. 75-121.
Calderero F, Eugenio F, Marcello J, Marqués F. Multispectral Cooperative Partition Sequence Fusion for Joint Classification and Hierarchical Segmentation. Geoscience and Remote Sensing Letters, IEEE. 2012;9:1012-1016.
Calderero F, Marqués F. Region merging parameter dependency as information diversity to create sparse hierarchies of partitions. In 2010 IEEE International Conference on Image Processing. 2010. pp. 2237–2240.
Calderero F, Marqués F, Marcello J, Eugenio F. Hierarchical segmentation of vegetation areas in high spatial resolution images by fusion of multispectral information. In 2009 IEEE International Geoscience and Remote Sensing Symposium. 2009. pp. 232–235.
Calderero F, Marqués F. Region merging techniques using information theory statistical measures. IEEE transactions on image processing. 2010;19:1567–1586.

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