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] . 3D Medical Image Synthesis using Generative Adversarial Networks. In ACM Europe Celebration of Women in Computing, womENcourage 2017, Barcelona, Spain. 2017.
. 3D Point Cloud Segmentation Using a Fully Connected Conditional Random Field. In The 25th European Signal Processing Conference (EUSIPCO 2017). Kos island, Greece: Eurasip/IEEE; 2017. 
(2.34 MB)
(2.34 MB). Active Deep Learning for Medical Imaging Segmentation. . 2017. (2.84 MB)
(2.84 MB). Active Deep Learning for Medical Imaging Segmentation. In Medical Image meets NIPS 2017 Workshop. 2017. (187.43 KB)
(187.43 KB). Artificial intelligence suggests recipes based on food photos. Boston: MIT News; 2017.
. Augmented V-Net for infant brain segmentation. In MICCAI Grand Challenge on 6-month Infant Brain MRI Segmentation, MICCAI 2017. 2017.
. Augmented V-Net for White Matter Hyperintensities segmentation. In WMH Segmentation Challenge, Brain-lesion Workshop, MICCAI 2017 . 2017.
. Class Weighted Convolutional Features for Visual Instance Search. In 28th British Machine Vision Conference (BMVC). London, UK; 2017. (3.56 MB)
(3.56 MB). 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). Collaborative voting of 3D features for robust gesture estimation. In International Conference on Acoustics, Speech and Signal Processing. New Orleans, USA; 2017. (605.86 KB)
(605.86 KB). Cost-Effective Active Learning for Melanoma Segmentation. In ML4H: Machine Learning for Health Workshop at NIPS 2017. Long Beach, CA, USA; 2017. (521.82 KB)
(521.82 KB). Detection-aided liver lesion segmentation using deep learning. In ML4H: Machine Learning for Health Workshop at NIPS 2017. 2017. (1 MB)
(1 MB). Detection-aided medical image segmentation using deep learning. . 2017. (7.07 MB)
(7.07 MB). Disentangling Motion, Foreground and Background Features in Videos. In CVPR 2017 Workshop Brave New Motion Representations. 2017. (370.64 KB)
(370.64 KB). 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)
(576.67 KB). Efficient Combination of Pairwise Feature Networks. In: . Neural Connectomics Challenge. Springer International Publishing; 2017.
. Fine-tuning of CNN models for Instance Search with Pseudo-Relevance Feedback. Long Beach, CA, USA: NIPS 2017 Women in Machine Learning Workshop; 2017. (341.96 KB)
(341.96 KB). From Pixels to Sentiment: Fine-tuning CNNs for Visual Sentiment Prediction. Image and Vision Computing. 2017;. (1.92 MB)
(1.92 MB). Hierarchical Object Detection with Deep Reinforcement Learning. In Deep Learning for Image Processing Applications. Amsterdam, The Netherlands: IOS Press; 2017.
. Hierarchical stack filtering: a bitplane-based algorithm for massively parallel processors. Journal of Real-Time Image Processing. 2017;. (868.82 KB)
(868.82 KB). The Impact of Segmentation on the Accuracy and Sensitivity of a Melanoma Classifier based on Skin Lesion Images. In Annual Meeting of the Society of Imaging Informatics in Medicine (SIIM). Pittsburgh, PA, USA: Society of Imaging Informatics for Medicine; 2017. (433.28 KB)
(433.28 KB). The impact of visual saliency prediction in image classification. . 2017. (828.66 KB)
(828.66 KB). La meitat de les notícies que consumirem el 2022 seran falses. Sant Joan Despí: Corporació Catalana de Mitjans Audiovisuals; 2017.