22 citations · 34 across the 7 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…
cs.CV2021★ 7 cited
W2WNet: a two-module probabilistic Convolutional Neural Network with embedded data cleansing functionality
Francesco Ponzio, Enrico Macii, Elisa Ficarra +1
Convolutional Neural Networks (CNNs) are supposed to be fed with only high-quality annotated datasets. Nonetheless, in many real-world scenarios, such high quality is very hard to…