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Enhancing classification performance of convolutional neural networks for prostate cancer detection on magnetic resonance images: a study with the semantic learning machine., , , и . GECCO (Companion), стр. 381-382. ACM, (2019)Automated Prostate Gland Segmentation Based on an Unsupervised Fuzzy C-Means Clustering Technique Using Multispectral T1w and T2w MR Imaging., , , , , , и . Information, 8 (2): 49 (2017)Estimation of Kinetic Reaction Constants: Exploiting Reboot Strategies to Improve PSO's Performance., , , , и . CIBB, том 10834 из Lecture Notes in Computer Science, стр. 92-102. Springer, (2017)CT Radiomic Features and Clinical Biomarkers for Predicting Coronary Artery Disease., , , , , и . Cogn. Comput., 15 (1): 238-253 (января 2023)Combining Noise-to-Image and Image-to-Image GANs: Brain MR Image Augmentation for Tumor Detection., , , , , , , и . IEEE Access, (2019)MADGAN: unsupervised medical anomaly detection GAN using multiple adjacent brain MRI slice reconstruction., , , , , , , , , и . BMC Bioinform., 22-S (2): 31 (2021)A Novel Bio-Inspired Approach for High-Performance Management in Service-Oriented Networks., , , и . IEEE Trans. Emerg. Top. Comput., 9 (4): 1709-1722 (2021)Calibrating the Dice Loss to Handle Neural Network Overconfidence for Biomedical Image Segmentation., , , , , и . J. Digit. Imaging, 36 (2): 739-752 (апреля 2023)USE-Net: Incorporating Squeeze-and-Excitation blocks into U-Net for prostate zonal segmentation of multi-institutional MRI datasets., , , , , , , , , и 5 other автор(ы). Neurocomputing, (2019)3D deformable registration of longitudinal abdominopelvic CT images using unsupervised deep learning., , , , , , , , , и . CoRR, (2020)