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Conference Paper
Blanco JA, Pardàs M, Casas JR, Paugam R, Àgueda A, Wagner J, et al.. Estimation of 3D Shape and Volume of Fire Plumes from Multiple Views. In 4th European Symposium on Fire Safety Science. Barcelona: IOP J. Phys.: Conf. Ser.; 2024.  (708.59 KB)
Fernàndez D, Rimmek JMarco, Espadaler J, Garolera B, Barja A, Codina M, et al.. Enhancing Online Knowledge Graph Population with Semantic Knowledge. In 19th International Semantic Web Conference (ISWC). Virtual; 2020.
Torres L, Casas JR, Campins J. An efficient technique of texture representation in segmentation-based image coding schemes. In IEEE INTERNATIONAL CONFERENCE ON IMAGE PROCESSING. 1995. pp. 588–591.
Torres L, Casas JR, Campins J. An efficient technique of texture representation in segmentation-based image coding schemes. In IEEE INTERNATIONAL CONFERENCE ON IMAGE PROCESSING. 1995. pp. 588–591.
Casas JR, Torres L, Jareño M. Efficient coding of residual images. In SPIE Visual Communications '93. Cambridge, MA: SPIE; 1993. pp. 694–705.
Giró-i-Nieto X, Marqués F, Casas JR. The edition of the Wikipedia as an academic activity. In 4rt. Congrés Internacional de Docència Unversitària i Innovació. Barcelona, Catalonia; 2006. p. –.  (801.45 KB)
Marsden M, Mohedano E, McGuinness K, Calafell A, Giró-i-Nieto X, O'Connor N, et al.. Dublin City University and Partners' Participation in the INS and VTT Tracks at TRECVid 2016. In TRECVID Workshop 2016. Gaithersburg, MD, USA; 2016.
Campos V, Salvador A, Giró-i-Nieto X, Jou B. Diving Deep into Sentiment: Understanding Fine-tuned CNNs for Visual Sentiment Prediction. In 1st International Workshop on Affect and Sentiment in Multimedia. Brisbane, Australia: ACM; 2015.  (506.22 KB)
Campos V, Sastre F, Yagües M, Bellver M, Giró-i-Nieto X, Torres J. Distributed training strategies for a computer vision deep learning algorithm on a distributed GPU cluster. In International Conference on Computational Science (ICCS). Zurich, Switzerland: Elsevier; 2017.  (576.67 KB)
Lin X, Campos V, Giró-i-Nieto X, Torres J, Canton-Ferrer C. Disentangling Motion, Foreground and Background Features in Videos. In CVPR 2017 Workshop Brave New Motion Representations. 2017.  (370.64 KB)
Lin X, Campos V, Giró-i-Nieto X, Torres J, Canton-Ferrer C. Disentangling Motion, Foreground and Background Features in Videos. In CVPR 2017 Workshop Brave New Motion Representations. 2017.  (370.64 KB)
Casas JR, Torres L. Diseño de filtros de imagen con funciones de transferencia. In VI Simposium Nacional de la Unión Científica Internacional de Radio. 1991. pp. 965–969.
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.
Salembier P, O'Connor N, Correa P, Ward L. The DICEMAN description schemes for still images and video sequences. In Workshop on Image Analysis for Multimedia Application Services, WIAMIS’99. Berlin, Germany; 1999. pp. 25–34.  (718.69 KB)
Sayrol E, Soriano M, Fernandez M, Casanelles J, Tomàs J. Development of a platform offering video copyright protection and security against illegal distribution. In Security, Steganography, and Watermarking of Multimedia Contents. 2005. pp. 76–83.
Casamitjana A, Petrone P, Falcon C, Artigues M, Operto G, Cacciaglia R, et al.. Detection of Amyloid Positive Cognitively unimpaired individuals using voxel-based machine learning on structural longitudinal brain MRI. In Alzheimer's Association International Conference. 2019.
Casamitjana A, Petrone P, Falcon C, Artigues M, Operto G, Cacciaglia R, et al.. Detection of Amyloid Positive Cognitively unimpaired individuals using voxel-based machine learning on structural longitudinal brain MRI. In Alzheimer's Association International Conference. 2019.
Baldrich A, Paugam R, Casas JR, Pardàs M, Àgueda A, Parsons R, et al.. Deep learning-based methodology for smoke plume segmentation of wildfire images. In 14th International Symposium on Fire Safety Science (IAFSS2023). Tsukuba, Japan: International Association for Fire Safety Science (IAFSS); 2023.  (144.69 KB)
Casamitjana A, Sala-Llonch R, Tudela R, Andrés A, Orío S, Casas JR, et al.. Deep Learning CT segmentation for dosimetry in postoperative endometrial carcinoma treatment. In XLI Congreso Anual de la Sociedad Española de Ingeniería Biomédica. Cartagena: Ediciones UPCT. Universidad Politécnica de Cartagena; 2023.  (236.12 KB)
Casamitjana A, Sala-Llonch R, Tudela R, Andrés A, Orío S, Casas JR, et al.. Deep Learning CT segmentation for dosimetry in postoperative endometrial carcinoma treatment. In XLI Congreso Anual de la Sociedad Española de Ingeniería Biomédica. Cartagena: Ediciones UPCT. Universidad Politécnica de Cartagena; 2023.  (236.12 KB)
Casamitjana A, Sala-Llonch R, Tudela R, Andrés A, Orío S, Casas JR, et al.. Deep Learning CT segmentation for dosimetry in postoperative endometrial carcinoma treatment. In XLI Congreso Anual de la Sociedad Española de Ingeniería Biomédica. Cartagena: Ediciones UPCT. Universidad Politécnica de Cartagena; 2023.  (236.12 KB)
Salvador A, Zeppelzauer M, Manchon-Vizuete D, Calafell A, Giró-i-Nieto X. Cultural Event Recognition with Visual ConvNets and Temporal Models. In CVPR ChaLearn Looking at People Workshop 2015. 2015.  (1.09 MB)
Salvador A, Carlier A, Giró-i-Nieto X, Marques O, Charvillat V. Crowdsourced Object Segmentation with a Game. In ACM Workshop on Crowdsourcing for Multimedia (CrowdMM). Barcelona; 2013.  (1.22 MB)
Salvador A, Carlier A, Giró-i-Nieto X, Marques O, Charvillat V. Crowdsourced Object Segmentation with a Game. In ACM Workshop on Crowdsourcing for Multimedia (CrowdMM). Barcelona; 2013.  (1.22 MB)
Górriz M, Giró-i-Nieto X, Carlier A, Faure E. Cost-Effective Active Learning for Melanoma Segmentation. In ML4H: Machine Learning for Health Workshop at NIPS 2017. Long Beach, CA, USA; 2017.  (521.82 KB)

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