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2019
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)
Herrera-Palacio A. Recurrent Instance Segmentation with Linguistic Referring Expressions. Giró-i-Nieto X, Ventura C, Silberer C. 2019.  (3.6 MB)
Gullón N, Vilaplana V. Retinal lesions segmentation using CNNs and adversarial training. In International Symposium on Biomedical Imaging (ISBI 2019). 2019.
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)
Casamitjana A, Petrone P, Molinuevo JL, Gispert JD, Vilaplana V. Shared latent structures between imaging features and biomarkers in early stages of Alzheimer's disease: a predictive study. IEEE Journal of Biomedical and Health Informatics. 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;.
Casamitjana A. Study of early stages of Alzheimer’s disease using magnetic resonance imaging. Vilaplana V. Signal Theory and Communications. [Barcelona]: Universitat Politècnica de Catalunya; 2019.
Casals R. Synthesis of acne images for data augmentation with generative adversarial networks. Vilaplana V. 2019.
Gené-Mola J, Vilaplana V, Rosell-Polo JR, Morros JR, Ruiz-Hidalgo J, Gregorio E. 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)
Herrera-Palacio A, Ventura C, Giró-i-Nieto X. Video Object Linguistic Grounding. In ACM Multimedia Workshop on Multimodal Understanding and Learning for Embodied Applications (MULEA). Nice, France: ACM; 2019.  (441.12 KB)
2018
Xu Z, Vilaplana V, Morros JR. Action Tube Extraction based 3D -CNN for RGB-D Action Recognition. In International Conference on Content-Based Multimedia Indexing CBMI 2018. 2018.  (3.09 MB)
Tochon G, Dalla Mura M, Veganzones MA, Valero S, Salembier P, Chanussot J. Advances in utilization of hierarchical representations in remote sensing data analysis. In Reference Module in Earth Systems and Environmental Sciences. Elsevier; 2018. pp. 77-107.
Tochon G, Dalla Mura M, Veganzones MA, Valero S, Salembier P, Chanussot J. Advances in utilization of hierarchical representations in remote sensing data analysis. In Reference Module in Earth Systems and Environmental Sciences. Elsevier; 2018. pp. 77-107.
Artigot JMartínez. Automatic fruit classification using deep learning. Morros JRamon, Vilaplana V. 2018.
Roselló CBonín. Brain lesion segmentation using Convolutional Neuronal Networks. Casamitjana A, Vilaplana V. 2018.  (3.15 MB)
Sánchez I, Vilaplana V. Brain MRI Super-Resolution using Generative Adversarial Networks. In International Conference on Medical Imaging with Deep Learning. Amsterdam, The Netherlands; 2018.
Casamitjana A, Catà M, Sánchez I, Combalia M, Vilaplana V. Cascaded V-Net Using ROI Masks for Brain Tumor Segmentation. In Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries. BrainLes 2017. Crimi A., Bakas S., Kuijf H., Menze B., Reyes M. (eds). Cham: Springer; 2018. pp. 381-391.
Petrone P, Casamitjana A, Falcon C, Artigues M, Operto G, Skouras S, et al.. Characteristic Brain Volumetric Changes in the AD Preclinical Signature. In Alzheimer's Association International Conference. Chicago, USA; 2018.
Petrone P, Casamitjana A, Falcon C, Artigues M, Operto G, Skouras S, et al.. Characteristic Brain Volumetric Changes in the AD Preclinical Signature. Alzheimer's & Dementia: The Journal of the Alzheimer's Association. 2018;14(7):P1235.
Pelegrí JBustos. Clasificación de imágenes histológicas mediante redes neuronales convolucionales. Combalia M, Vilaplana V. 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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