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The Impact of Segmentation on the Accuracy and Sensitivity of a Melanoma Classifier based on Skin Lesion Images. In Annual Meeting of the Society of Imaging Informatics in Medicine (SIIM). Pittsburgh, PA, USA: Society of Imaging Informatics for Medicine; 2017. (433.28 KB)
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. . Image Segmentation Evaluation and Its Application to Object Detection. . [Barcelona]: Universitat Politècnica de Catalunya, BarcelonaTech; 2014. (48.44 MB)
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. Image compression with generalized lifting and partial knowledge of the signal pdf. In IEEE International Conference on Image Processing, ICIP 2008. San Diego, USA; 2008. pp. 250–254. (830.94 KB)
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. Image and video processing tools for HCI. In Multimodal signal processing: theory and applications for human-computer interaction. 2009. pp. 93–118.
. . Image and Video Object Segmentation in Low Supervision Scenarios. . Computer Architectures. [Barcelona]: Universitat Politecnica de Catalunya; 2021.
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. Image Analysis and Understanding Based on Information Theoretical Region Merging Approaches for Segmentation and Cooperative Fusion. In Handbook of Research on Computational Intelligence for Engineering, Science, and Business. IGI Global; 2012. pp. 75-121.
. 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.
. Identifying brain ageing trajectories using variational autoencoders with regression model in neuroimaging data stratified by sex and validated against dementia-related risk factors. In 7th International Workshop on PRedictive Intelligence in MEdicine, MICCAI 2024. In Press.
. Hyperspectral image segmentation using binary partition trees. In IEEE International Conference on Image Processing, ICIP 2011. Brussels, Belgium; 2011. pp. 1273–1276. (669.46 KB)
. Hyperspectral image representation and Processing with Binary Partition Trees. . Universitat Politècnica de Catalunya (UPC); 2011. (20.92 MB)
. Hyperspectral image representation and processing with Binary Partition Trees. IEEE Transactions on Image Processing. 2013;22(4):1430 - 1443. (1.81 MB)
. Hyper-Representations: Learning from Populations of Neural Networks. . Unievrsity of St. Gallen. 2024. (18.12 MB)
. Hyper-Representations as Generative Models: Sampling Unseen Neural Network Weights. In NeurIPS 2022 - Neural Information Processing Systems. 2022. (4.6 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)
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