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Few-shot learning is an established topic in natural images for years, but few work is attended to histology images, which is of high clinical value since well-labeled datasets and rare abnormal samples are expensive to collect.
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Kushagra Mahajan, Monika Sharma, and Lovekesh Vig · 2020
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Yonglong Tian, Yue Wang, Dilip Krishnan, Joshua B Tenenbaum, and Phillip Isola · 2020
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Understanding contrastive representation learning through alignment and uniformity on the hypersphere
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Fhist: A benchmark for few-shot classification of histological images
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Yulin Wang, Gao Huang, Shiji Song, Xuran Pan, Yitong Xia, and Cheng Wu · 2021
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Free lunch for few-shot learning: Distribution calibration
Shuo Yang, Lu Liu, and Min Xu · 2021
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