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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.
Górriz M, Aparicio A, Raventós B, López-Codina D, Vilaplana V, Sayrol E. Leishmaniasis Parasite Segmentation and Classification Using Deep Learning. In International Conference on Articulated Motion and Deformable Objects. Palma, Spain; 2018.
Górriz M, Aparicio A, Raventós B, Vilaplana V, Sayrol E, López-Codina D. Leishmaniasis Parasite Segmentation and Classification Using Deep Learning. In Articulated Motion and Deformable Objects. Springer International Publishing; 2018. pp. 53-62.
Combalia M, Vilaplana V. Monte-Carlo Sampling applied to Multiple Instance Learning for Histological Image Classification. In Workshop on Deep Learning in Medical Image Analysis, MICCAI. Granada, Spain; 2018.
Combalia M, Vilaplana V. Monte-Carlo Sampling Applied to Multiple Instance Learning for Histological Image Classification. In Deep Learning in Medical Image Analysis and Multimodal Learning for Clinical Decision Support. Springer International Publishing; 2018. pp. 274-281.
Combalia M, Vilaplana V. Monte-Carlo Sampling applied to Multiple Instance Learning for Whole Slide Image Classification. In International Conference on Medical Imaging with Deep Learning. Amsterdam, The Netherlands; 2018.
Casamitjana A, Petrone P, Tucholka A, Falcon C, Skouras S, Molinuevo JLuis, et al.. MRI-Based Screening of Preclinical Alzheimer's Disease for Prevention Clinical Trials. Journal of Alzheimer's Disease. 2018;64(4).
Shou Z, Pan J, Chan J, Miyazawa K, Mansour H, Vetro A, et al.. Online Action Detection in Untrimmed, Streaming Videos. In European Conference on Computer Vision (ECCV). Munich, German; 2018.  (450.1 KB)

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