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. BCN20000: Dermoscopic Lesions in the Wild. In International Skin Imaging Collaboration (ISIC) Challenge on Dermoscopic Skin Lesion Analysis 2019. 2019.
. BCN20000: Dermoscopic Lesions in the Wild. In International Skin Imaging Collaboration (ISIC) Challenge on Dermoscopic Skin Lesion Analysis 2019. 2019.
. Correspondence matching in unorganized 3D point clouds using Convolutional Neural Networks. Image and Vision Computing. 2019;83-84. 
(3.95 MB)
(3.95 MB). 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)
(980.9 KB). 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)
(980.9 KB). Fruit Detection in an Apple Orchard Using a Mobile Terrestrial Laser Scanner. Biosystems Engineering. 2019;187.
. Fruit Detection in an Apple Orchard Using a Mobile Terrestrial Laser Scanner. Biosystems Engineering. 2019;187.
. A Generative Dialogue System for Reminiscence Therapy. . 2019. (4.89 MB)
(4.89 MB). 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)
(749.7 KB). 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)
(749.7 KB). Inverse Cooking: Recipe Generation from Food Images. In CVPR. Long Beach, CA, USA: OpenCVF / IEEE; 2019.
. KFuji RGB-DS database: Fuji apple multi-modal images for fruit detection with color, depth and range-corrected IR data. Data in Brief. 2019;. (2.43 MB)
(2.43 MB). KFuji RGB-DS database: Fuji apple multi-modal images for fruit detection with color, depth and range-corrected IR data. Data in Brief. 2019;. (2.43 MB)
(2.43 MB). Multi-modal Deep Learning for Fuji Apple Detection Using RGB-D Cameras and their Radiometric Capabilities. Computers and Electronics in Agriculture. 2019;162.
. Multi-modal Deep Learning for Fuji Apple Detection Using RGB-D Cameras and their Radiometric Capabilities. Computers and Electronics in Agriculture. 2019;162.
. Multi-View 3D Face Reconstruction in the Wild using Siamese Networks. In ICCV 2019 Workshop on 3D Face Alignment in the Wild Challenge Workshop (3DFAW). Seoul, South Corea: IEEE/CVF; 2019. (227.12 KB)
(227.12 KB). 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)
(3.97 MB). 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)
(3.97 MB). Prediction of a second clinical event in CIS patients by combining lesion and brain features. In Congress of the European Comitee for Treatment and Research in Multiple Sclerosis (ECTRIMS 2019). 2019.
. Residual Attention Graph Convolutional Network for Geometric 3D Scene Classification. In IEEE Conference on Computer Vision Workshop (ICCVW). Seoul, Korea: IEEE; 2019. (314.43 KB)
(314.43 KB). Self-registered lidar and polarimetric images in real-time: application to detection of small objects at sea. In 7th Workshop on Active Imaging. Saint-Louis, France: French-German Research Institute of Saint-Louis (ISL); 2019.
. Self-registered lidar and polarimetric images in real-time: application to detection of small objects at sea. In 7th Workshop on Active Imaging. Saint-Louis, France: French-German Research Institute of Saint-Louis (ISL); 2019.
. Standardized Assessment of Automatic Segmentation of White Matter Hyperintensities; Results of the WMH Segmentation Challenge. IEEE Transactions on Medical Imaging. 2019;.
. Uso de redes neuronales convolucionales para la detección remota de frutos con cámaras RGB-D. In Congreso Ibérico de Agroingeniería. Huesca: Universidad de Zaragoza (UZA); 2019. (1.21 MB)
(1.21 MB)