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2019
Wang L, Nie D, Li G, Puybareau E, Dolz J, Zhang Q, et al.. Benchmark on Automatic 6-month-old Infant Brain Segmentation Algorithms: The iSeg-2017 Challenge. IEEE Transactions on Medical Imaging. 2019;.
Wang L, Nie D, Li G, Puybareau E, Dolz J, Zhang Q, et al.. Benchmark on Automatic 6-month-old Infant Brain Segmentation Algorithms: The iSeg-2017 Challenge. IEEE Transactions on Medical Imaging. 2019;.
Wang L, Nie D, Li G, Puybareau E, Dolz J, Zhang Q, et al.. Benchmark on Automatic 6-month-old Infant Brain Segmentation Algorithms: The iSeg-2017 Challenge. IEEE Transactions on Medical Imaging. 2019;.
Bellver M, Salvador A, Torres J, Giró-i-Nieto X. Budget-aware Semi-Supervised Semantic and Instance Segmentation. In CVPR 2019 DeepVision Workshop. Long Beach, CA, USA: OpenCVF; 2019.  (6.59 MB)
Balibrea M. Deep learning for semantic segmentation of airplane hyperspectral imaging. Salgueiro L, Vilaplana V. 2019.
Roisman A, Navarro A, Clot G, Castellano G, Gonzalez-Farre B, Pérez-Galan P, et al.. Differential expression of long non-coding RNAs related to proliferation and histological diversity in follicular lymphomas. British Journal of Haematology. 2019;184(3):373-383.  (980.9 KB)
Roisman A, Navarro A, Clot G, Castellano G, Gonzalez-Farre B, Pérez-Galan P, et al.. Differential expression of long non-coding RNAs related to proliferation and histological diversity in follicular lymphomas. British Journal of Haematology. 2019;184(3):373-383.  (980.9 KB)
Ramon E, Ruiz G, Batard T, Giró-i-Nieto X. Hyperparameter-Free Losses for Model-Based Monocular Reconstruction. In ICCV 2019 Workshop on Geometry Meets Deep Learning. Seoul, South Corea: IEEE / Computer Vision Foundation; 2019.  (749.7 KB)
LLadós J, Bou E, Bressan M, Sala O, Giró-i-Nieto X. The pillars of the Computer Vision Catalan Alliance. 2019.
LLadós J, Bou E, Bressan M, Sala O, Giró-i-Nieto X. The pillars of the Computer Vision Catalan Alliance. 2019.
Ramon E, Villar J, Ruiz G, Batard T, Giró-i-Nieto X. Plug-and-Train Loss for Model-Based Single View 3D Reconstruction. BMVA Technical Meeting: 3D vision with Deep Learning. London, UK: UPC; 2019.  (3.97 MB)
Herrera-Palacio A, Ventura C, Silberer C, Sorodoc I-T, Boleda G, Giró-i-Nieto X. Recurrent Instance Segmentation using Sequences of Referring Expressions. In NeurIPS workshop on Visually Grounded Interaction and Language (ViGIL). Vancouver, Canada; 2019.  (1.13 MB)
Ventura C, Bellver M, Girbau A, Salvador A, Marqués F, Giró-i-Nieto X. RVOS: End-to-End Recurrent Network for Video Object Segmentation. In CVPR. Long Beach, CA, USA: OpenCVF / IEEE; 2019.  (5.76 MB)
Kuijf H, Biesbroek M, de Bresser J, Heinen R, Andermatt S, Bento M, et al.. Standardized Assessment of Automatic Segmentation of White Matter Hyperintensities; Results of the WMH Segmentation Challenge. IEEE Transactions on Medical Imaging. 2019;.
Kuijf H, Biesbroek M, de Bresser J, Heinen R, Andermatt S, Bento M, et al.. Standardized Assessment of Automatic Segmentation of White Matter Hyperintensities; Results of the WMH Segmentation Challenge. IEEE Transactions on Medical Imaging. 2019;.
Kuijf H, Biesbroek M, de Bresser J, Heinen R, Andermatt S, Bento M, et al.. Standardized Assessment of Automatic Segmentation of White Matter Hyperintensities; Results of the WMH Segmentation Challenge. IEEE Transactions on Medical Imaging. 2019;.
Kuijf H, Biesbroek M, de Bresser J, Heinen R, Andermatt S, Bento M, et al.. Standardized Assessment of Automatic Segmentation of White Matter Hyperintensities; Results of the WMH Segmentation Challenge. IEEE Transactions on Medical Imaging. 2019;.
Kuijf H, Biesbroek M, de Bresser J, Heinen R, Andermatt S, Bento M, et al.. Standardized Assessment of Automatic Segmentation of White Matter Hyperintensities; Results of the WMH Segmentation Challenge. IEEE Transactions on Medical Imaging. 2019;.
Kuijf H, Biesbroek M, de Bresser J, Heinen R, Andermatt S, Bento M, et al.. Standardized Assessment of Automatic Segmentation of White Matter Hyperintensities; Results of the WMH Segmentation Challenge. IEEE Transactions on Medical Imaging. 2019;.
Bellot P, Salembier P, Pham NC, Meyer PE. Unsupervised GRN Ensemble. In Sanguinetti G., Huynh-Thu V. (eds) Methods in Molecular Biology . New York, NY: Springer science, Humana Press; 2019. pp. 283-302.
Granero M. A Video Database for Analyzing Affective Physiological Responses. Borth D, Weber B, Giró-i-Nieto X. 2019.  (23.66 MB)
Fernàndez D, Bou E, Giró-i-Nieto X. VLX-Stories: a Semantically Linked Event platform for media publishers. In Proceedings of the ISWC 2019 Satellite Tracks (Posters & Demonstrations, Industry, and Outrageous Ideas) co-located with 18th International Semantic Web Conference (ISWC 2019). Auckland, New Zealand: CEUR Workshop Proceeedings; 2019.  (759.51 KB)
Fernàndez D, Bou E, Giró-i-Nieto X. VLX-Stories: building an online Event Knowledge Base with Emerging Entity detection. In The Semantic Web – ISWC 2019. Auckland, New Zealand: Springer, Cham; 2019. pp. 382-399.  (1.42 MB)
2018
Batiste G. Generative Adversarial Networks for Anomaly Detection in Images. Vilaplana V. 2018.
Bakas S, Reyes M, Jakab A, Bauer S, Casamitjana A, Vilaplana V, et al.. Identifying the best machine learning algorithms for brain tumor segmentation, progression assessment, and overall survival prediction in the BRATS challenge. In MICCAI - Multimodal Brain Tumor Segmentation Challenge. 2018.

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