A review: Deep learning for medical image segmentation using multi-modality fusion von Zhou, Tongxue, Ruan, Su, Canu, Stéphane

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Latent Correlation Representation Learning for Brain Tumor Segmentation With Missing MRI Modalities von Zhou, Tongxue, Canu, Stephane, Vera, Pierre, Ruan, Su

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Automatic COVID‐19 CT segmentation using U‐Net integrated spatial and channel attention mechanism von Zhou, Tongxue, Canu, Stéphane, Ruan, Su

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A Tri-Attention fusion guided multi-modal segmentation network von Zhou, Tongxue, Ruan, Su, Vera, Pierre, Canu, Stéphane

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Feature-enhanced generation and multi-modality fusion based deep neural network for brain tumor segmentation with missing MR modalities von Zhou, Tongxue, Canu, Stéphane, Vera, Pierre, Ruan, Su

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Improving Unsupervised Domain Adaptive Re-Identification Via Source-Guided Selection of Pseudo-Labeling Hyperparameters von Dubourvieux, Fabian, Loesch, Angelique, Audigier, Romaric, Ainouz, Samia, Canu, Stephane

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Missing Data Imputation via Conditional Generator and Correlation Learning for Multimodal Brain Tumor Segmentation von Zhou, Tongxue, Vera, Pierre, Canu, Stéphane, Ruan, Su

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Fusion based on attention mechanism and context constraint for multi-modal brain tumor segmentation von Zhou, Tongxue, Canu, Stéphane, Ruan, Su

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Learning SVM in Kreĭn Spaces von Loosli, Gaelle, Canu, Stephane, Ong, Cheng Soon

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SimpleMKL von Rakotomamonjy, Alain, Bach, Francis, Canu, Stephane, Grandvalet, Yves

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Data based loss estimation of the mean of a spherical distribution with a residual vector von Canu, Stéphane, Fourdrinier, Dominique

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Recovering Sparse Signals With a Certain Family of Nonconvex Penalties and DC Programming von Gasso, G., Rakotomamonjy, A., Canu, S.

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Nonconvex Regularizations for Feature Selection in Ranking With Sparse SVM von Laporte, Léa, Flamary, Rémi, Canu, Stéphane, Déjean, Sébastien, Mothe, Josiane

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A Physically Admissible Stokes Vector Reconstruction in Linear Polarimetric Imaging von Le Guyader, Carole, Ainouz, Samia, Canu, Stéphane

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A formal approach to good practices in Pseudo-Labeling for Unsupervised Domain Adaptive Re-Identification von Dubourvieux, Fabian, Audigier, Romaric, Loesch, Angélique, Ainouz, Samia, Canu, Stéphane

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Operator-valued Kernels for Learning from Functional Response Data von Kadri, Hachem, Duflos, Emmanuel, Preux, Philippe, Canu, Stéphane, Rakotomamonjy, Alain, Audiffren, Julien

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Machine Learning and Knowledge Discovery in Databases: European Conference, ECML PKDD 2022, Grenoble, France, September 19-23, 2022, Proceedings, Part I von Amini, Massih-Reza, Canu, Stéphane, Fischer, Asja, Guns, Tias, Kralj Novak, Petra, Tsoumakas, Grigorios

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Machine Learning and Knowledge Discovery in Databases: European Conference, ECML PKDD 2022, Grenoble, France, September 19-23, 2022, Proceedings, Part III von Amini, Massih-Reza, Canu, Stéphane, Fischer, Asja, Guns, Tias, Kralj Novak, Petra, Tsoumakas, Grigorios

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Machine Learning and Knowledge Discovery in Databases: European Conference, ECML PKDD 2022, Grenoble, France, September 19-23, 2022, Proceedings, Part IV von Amini, Massih-Reza, Canu, Stéphane, Fischer, Asja, Guns, Tias, Kralj Novak, Petra, Tsoumakas, Grigorios

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Machine Learning and Knowledge Discovery in Databases: European Conference, ECML PKDD 2022, Grenoble, France, September 19-23, 2022, Proceedings, Part VI von Amini, Massih-Reza, Canu, Stéphane, Fischer, Asja, Guns, Tias, Kralj Novak, Petra, Tsoumakas, Grigorios

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