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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;.
Domenech T. Clasificación de imágenes dermatoscópicas utilizando Redes Neuronales Convolucionales e información de metadatos. Vilaplana V. 2019.
Tarrés L. Clasificación de lesiones de piel con un ensemble de redes neuronales residuales. Vilaplana V, Combalia M. 2019.
Isart A, Espasa M, Vilaplana V, Sayrol E. CNN-based bacilli detection in sputum samples for tuberculosis diagnosis. In International Symposium on Biomedical Imaging (ISBI 2019). 2019.
Balibrea M. Deep learning for semantic segmentation of airplane hyperspectral imaging. Salgueiro L, Vilaplana V. 2019.
Combalia M, Pérez-Anker J, García-Herrera A, Alos L, Vilaplana V, Marques F, et al.. Digitally Stained Confocal Microscopy through Deep Learning. In International Conference on Medical Imaging with Deep Learning (MIDL 2019). London; 2019.
Gené-Mola J, Gregorio E, Guevara J, Cheein FAuat, Sanz R, Escolà A, et al.. Fruit Detection in an Apple Orchard Using a Mobile Terrestrial Laser Scanner. Biosystems Engineering. 2019;187.
Domingo P. Interpretability of Deep Learning Models. Vilaplana V. 2019.
Gené-Mola J, Vilaplana V, Rosell-Polo JR, Morros JR, Ruiz-Hidalgo J, Gregorio E. 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)
Sala M, Soriguera F, Huillca K, Vilaplana V. Measuring traffic lane-changing by converting video into space-time still images. Computer-Aided Civil and Infrastructure Engineering. 2019;.
Gené-Mola J, Vilaplana V, Rosell-Polo JR, Morros JR, Ruiz-Hidalgo J, Gregorio E. Multi-modal Deep Learning for Fuji Apple Detection Using RGB-D Cameras and their Radiometric Capabilities. Computers and Electronics in Agriculture. 2019;162.
Ventura C, Varas D, Vilaplana V, Giró-i-Nieto X, Marques F. Multiresolution co-clustering for uncalibrated multiview segmentation. Signal Processing: Image Communication. 2019;.  (4.35 MB)
Mas I, Morros JR, Vilaplana V. Picking groups instead of samples: A close look at Static Pool-based Meta-Active Learning. In ICCV Workshop - MDALC 2019. Seoul, South Korea; 2019.  (911.15 KB)
Gullón N, Vilaplana V. Retinal lesions segmentation using CNNs and adversarial training. In International Symposium on Biomedical Imaging (ISBI 2019). 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;.
Casals R. Synthesis of acne images for data augmentation with generative adversarial networks. Vilaplana V. 2019.

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