47 citations · 64 across the 6 of their papers we have counts for
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eess.IV2021★ 1 cited
Learning Representations with Contrastive Self-Supervised Learning for Histopathology Applications
Karin Stacke, Jonas Unger, Claes Lundström +1
Unsupervised learning has made substantial progress over the last few years, especially by means of contrastive self-supervised learning. The dominating dataset for benchmarking se…
eess.IV2021
Unsupervised anomaly detection in digital pathology using GANs
Milda Pocevičiūtė, Gabriel Eilertsen, Claes Lundström
Machine learning (ML) algorithms are optimized for the distribution represented by the training data. For outlier data, they often deliver predictions with equal confidence, even t…