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. Correspondence matching in unorganized 3D point clouds using Convolutional Neural Networks. Image and Vision Computing. 2019;83-84. 
(3.95 MB)
(3.95 MB). Contrastive and attention-based multiple instance learning for the prediction of sentinel lymph node status from histopathologies of primary melanoma tumours. In Cancer Prevention through early detecTion (Caption) Workshop at 25th International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI 2022). 2022.
. Context Awareness triggered by Multiple Perceptual Analyzers. In Emerging Artificial Intelligence Applications in Computer Engineering. Amsterdam: IOS Press; 2007. pp. 371–383. (878.64 KB)
(878.64 KB). Connected Operators on 3D data for human body analysis. In 2011 IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops. 2011. pp. 9–14.
. Computers in the Human Interaction Loop. In Handbook on Ambient Intelligence and Smart Environments (AISE). Boston, MA: Springer; 2010. pp. 1071–1116.
. Computers in the Human Interaction Loop. In Handbook on Ambient Intelligence and Smart Environments (AISE). Boston, MA: Springer; 2010. pp. 1071–1116.
. Comparison of merging orders and pruning strategies for binary partition tree in hyperspectral data. In IEEE International Conference on Image Processing, ICIP 2010. Hong Kong, China; 2010. pp. 2565–2568. (142.72 KB)
(142.72 KB). Comparing Fixed and Adaptive Computation Time for Recurrent Neural Network. In International Conference on Learning Representations (ICLR). Vancouver, Canada; 2018. (515.54 KB)
(515.54 KB). A compact 3D representation for multi-view video. In 2011 International Conference on 3D Imaging. 2011. pp. 1–8. (4.14 MB)
(4.14 MB). Collaborative voting of 3D features for robust gesture estimation. In International Conference on Acoustics, Speech and Signal Processing. New Orleans, USA; 2017. (0 bytes)
(0 bytes). Co-filtering human interaction and object segmentation. . 2015. (1.82 MB)
(1.82 MB). Co-filtering human interaction and object segmentation. . 2015. (1.82 MB)
(1.82 MB). Co-filtering human interaction and object segmentation. . 2015. (1.82 MB)
(1.82 MB). Coding of significant features in very low bit-rate video systems. In SPIE'S Visual Communications'94. 1994. pp. 73–85.
. Coding of details in very low bit-rate video systems. IEEE transactions on circuits and systems for video technology. 1994;4(3):317–327. (1.51 MB)
(1.51 MB). Codificacion run-length de imagenes de detalle. In VIII Simposium Nacional de la Unión Científica Internacional de Radio. 1993. pp. 349–399.
. Clustering and Prediction of Adjective-Noun Pairs for Affective Computing. . 2016. (10.38 MB)
(10.38 MB). Clustering and Prediction of Adjective-Noun Pairs for Affective Computing. . 2016. (10.38 MB)
(10.38 MB). Closing the Loop: Continuous AI Model Improvement Through Pathologist-Guided Feedback. In 21st European Congress on Digital Pathology. Barcelona: The European Society of Digital and Integrative Pathology; 2025. (92.01 KB)
(92.01 KB). A closed-loop approach for tracking a humanoid robot using particle filtering and depth data. Intelligent Service Robotics. 2017;10(4):297–312. (88.92 KB)
(88.92 KB). A closed-loop approach for tracking a humanoid robot using particle filtering and depth data. Intelligent Service Robotics. 2017;10(4):297–312. (88.92 KB)
(88.92 KB). Click’n’Cut: Crowdsourced Interactive Segmentation with Object Candidates. In 3rd International ACM Workshop on Crowdsourcing for Multimedia (CrowdMM). Orlando, Florida (USA); 2014. (1017.73 KB)
(1017.73 KB). Click’n’Cut: Crowdsourced Interactive Segmentation with Object Candidates. In 3rd International ACM Workshop on Crowdsourcing for Multimedia (CrowdMM). Orlando, Florida (USA); 2014. (1017.73 KB)
(1017.73 KB)