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Weakly-supervised High-resolution Segmentation of Mammography Images for Breast Cancer Diagnosis.

, , , , , and . MIDL, volume 143 of Proceedings of Machine Learning Research, page 451-472. PMLR, (2021)

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Classifier-Agnostic Saliency Map Extraction., , and . AAAI, page 10087-10088. AAAI Press, (2019)Understanding differences in applying DETR to natural and medical images., , , , and . CoRR, (2024)A convolutional neural network for common coordinate registration of high-resolution histology images., , and . Bioinform., 37 (22): 4216-4226 (November 2021)Deep Neural Networks Improve Radiologists' Performance in Breast Cancer Screening., , , , , , , , , and 22 other author(s). CoRR, (2019)fastMRI: An Open Dataset and Benchmarks for Accelerated MRI., , , , , , , , , and 13 other author(s). CoRR, (2018)Improving the Ability of Deep Neural Networks to Use Information from Multiple Views in Breast Cancer Screening., , , , , and . MIDL, volume 121 of Proceedings of Machine Learning Research, page 827-842. PMLR, (2020)Characterizing and Overcoming the Greedy Nature of Learning in Multi-modal Deep Neural Networks., , , and . ICML, volume 162 of Proceedings of Machine Learning Research, page 24043-24055. PMLR, (2022)Exploiting diversity for efficient machine learning. University of Edinburgh, UK, (2018)British Library, EThOS.Composite Denoising Autoencoders., and . ECML/PKDD (1), volume 9851 of Lecture Notes in Computer Science, page 681-696. Springer, (2016)Understanding the robustness of deep neural network classifiers for breast cancer screening., , , , , , , and . CoRR, (2020)