most citedExploiting generative self-supervised learning for the assessment of biological images with lack of annotations: a COVID-19 case-study

22 citations · 22 across the 1 of their papers we have counts for

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eess.IV2021★ 22 cited

Exploiting generative self-supervised learning for the assessment of biological images with lack of annotations: a COVID-19 case-study

Alessio Mascolini, Dario Cardamone, Francesco Ponzio +2

Computer-aided analysis of biological images typically requires extensive training on large-scale annotated datasets, which is not viable in many situations. In this paper we prese…