activity
20182021
most citedSkin Lesion Synthesis with Generative Adversarial Networks

105 citations · 120 across the 3 of their papers we have counts for

collaborators

5 papers

eess.IV2021

GAN-Based Data Augmentation and Anonymization for Skin-Lesion Analysis: A Critical Review

Alceu Bissoto, Eduardo Valle, Sandra Avila

Despite the growing availability of high-quality public datasets, the lack of training samples is still one of the main challenges of deep-learning for skin lesion analysis. Genera…

cs.CV2020

Debiasing Skin Lesion Datasets and Models? Not So Fast

Alceu Bissoto, Eduardo Valle, Sandra Avila

Data-driven models are now deployed in a plethora of real-world applications - including automated diagnosis - but models learned from data risk learning biases from that same data…

cs.CV201915 cited

The Six Fronts of the Generative Adversarial Networks

Alceu Bissoto, Eduardo Valle, Sandra Avila

Generative Adversarial Networks fostered a newfound interest in generative models, resulting in a swelling wave of new works that new-coming researchers may find formidable to surf…

cs.CV2019105 cited

Skin Lesion Synthesis with Generative Adversarial Networks

Alceu Bissoto, Fábio Perez, Eduardo Valle +1

Skin cancer is by far the most common type of cancer. Early detection is the key to increase the chances for successful treatment significantly. Currently, Deep Neural Networks are…

cs.CV2018

Deep-Learning Ensembles for Skin-Lesion Segmentation, Analysis, Classification: RECOD Titans at ISIC Challenge 2018

Alceu Bissoto, Fábio Perez, Vinícius Ribeiro +3

This extended abstract describes the participation of RECOD Titans in parts 1 to 3 of the ISIC Challenge 2018 "Skin Lesion Analysis Towards Melanoma Detection" (MICCAI 2018). Altho…