195 citations · 1k across the 35 of their papers we have counts for
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The Performance of Transferability Metrics does not Translate to Medical Tasks
Levy Chaves, Alceu Bissoto, Eduardo Valle +1
Transfer learning boosts the performance of medical image analysis by enabling deep learning (DL) on small datasets through the knowledge acquired from large ones. As the number of…
Test-Time Selection for Robust Skin Lesion Analysis
Alceu Bissoto, Catarina Barata, Eduardo Valle +1
Skin lesion analysis models are biased by artifacts placed during image acquisition, which influence model predictions despite carrying no clinical information. Solutions that addr…
Even Small Correlation and Diversity Shifts Pose Dataset-Bias Issues
Alceu Bissoto, Catarina Barata, Eduardo Valle +1
Distribution shifts are common in real-world datasets and can affect the performance and reliability of deep learning models. In this paper, we study two types of distribution shif…
Artifact-Based Domain Generalization of Skin Lesion Models
Alceu Bissoto, Catarina Barata, Eduardo Valle +1
Deep Learning failure cases are abundant, particularly in the medical area. Recent studies in out-of-distribution generalization have advanced considerably on well-controlled synth…
An Evaluation of Self-Supervised Pre-Training for Skin-Lesion Analysis
Levy Chaves, Alceu Bissoto, Eduardo Valle +1
Self-supervised pre-training appears as an advantageous alternative to supervised pre-trained for transfer learning. By synthesizing annotations on pretext tasks, self-supervision…
Single-Training Collaborative Object Detectors Adaptive to Bandwidth and Computation
Juliano S. Assine, J. C. S. Santos Filho, Eduardo Valle
In the past few years, mobile deep-learning deployment progressed by leaps and bounds, but solutions still struggle to accommodate its severe and fluctuating operational restrictio…