105 citations · 248 across the 13 of their papers we have counts for
18 papers · 1 filter
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…
Seeing without Looking: Analysis Pipeline for Child Sexual Abuse Datasets
Camila Laranjeira, João Macedo, Sandra Avila +1
The online sharing and viewing of Child Sexual Abuse Material (CSAM) are growing fast, such that human experts can no longer handle the manual inspection. However, the automatic cl…
CIDEr-R: Robust Consensus-based Image Description Evaluation
Gabriel Oliveira dos Santos, Esther Luna Colombini, Sandra Avila
This paper shows that CIDEr-D, a traditional evaluation metric for image description, does not work properly on datasets where the number of words in the sentence is significantly…
Less is More: Sample Selection and Label Conditioning Improve Skin Lesion Segmentation
Vinicius Ribeiro, Sandra Avila, Eduardo Valle
Segmenting skin lesions images is relevant both for itself and for assisting in lesion classification, but suffers from the challenge in obtaining annotated data. In this work, we…