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Deep Multi-Scale U-Net Architecture and Noise-Robust Training Strategies for Histopathological Image Segmentation., , , , , , , , , и 1 other автор(ы). CoRR, (2022)Deep Multi-Scale U-Net Architecture and Label-Noise Robust Training Strategies for Histopathological Image Segmentation., , , , , , , , , и 1 other автор(ы). BIBE, стр. 91-96. IEEE, (2022)Robust Classification of Histology Images Exploiting Adversarial Auto Encoders., , , , , и . EMBC, стр. 2871-2874. IEEE, (2021)MoNuSAC2020: A Multi-Organ Nuclei Segmentation and Classification Challenge., , , , , , , , , и 48 other автор(ы). IEEE Trans. Medical Imaging, 40 (12): 3413-3423 (2021)Author's Reply to "MoNuSAC2020: A Multi-Organ Nuclei Segmentation and Classification Challenge"., , , , , и . IEEE Trans. Medical Imaging, 41 (4): 1000-1003 (2022)Overall Survival Prediction in Glioblastoma With Radiomic Features Using Machine Learning., , , , , , и . Frontiers Comput. Neurosci., (2020)A Novel Approach for Fully Automatic Intra-Tumor Segmentation With 3D U-Net Architecture for Gliomas., , , , , , , , и . Frontiers Comput. Neurosci., (2020)Combining Datasets with Different Label Sets for Improved Nucleus Segmentation and Classification., , , , , , , и . CoRR, (2023)EGFR Mutation Prediction of Lung Biopsy Images Using Deep Learning., , , , , , , и . BIOIMAGING, стр. 102-109. SCITEPRESS, (2023)Deep Learning Radiomics Algorithm for Gliomas (DRAG) Model: A Novel Approach Using 3D UNET Based Deep Convolutional Neural Network for Predicting Survival in Gliomas., , , , , , , и . BrainLes@MICCAI (2), том 11384 из Lecture Notes in Computer Science, стр. 369-379. Springer, (2018)