activity
20182022
most citedSkin Lesion Synthesis with Generative Adversarial Networks

105 citations · 189 across the 5 of their papers we have counts for

collaborators

7 papers

cs.CL202280 cited

Ignore Previous Prompt: Attack Techniques For Language Models

Fábio Perez, Ian Ribeiro

Transformer-based large language models (LLMs) provide a powerful foundation for natural language tasks in large-scale customer-facing applications. However, studies that explore t…

cs.CV2020

Print Defect Mapping with Semantic Segmentation

Augusto C. Valente, Cristina Wada, Deangela Neves +6

Efficient automated print defect mapping is valuable to the printing industry since such defects directly influence customer-perceived printer quality and manually mapping them is…

cs.CV2019

Solo or Ensemble? Choosing a CNN Architecture for Melanoma Classification

Fábio Perez, Sandra Avila, Eduardo Valle

Convolutional neural networks (CNNs) deliver exceptional results for computer vision, including medical image analysis. With the growing number of available architectures, picking…

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.LG20194 cited

Weakly Supervised Active Learning with Cluster Annotation

Fábio Perez, Rémi Lebret, Karl Aberer

In this work, we introduce a novel framework that employs cluster annotation to boost active learning by reducing the number of human interactions required to train deep neural net…

cs.CV2018

Data Augmentation for Skin Lesion Analysis

Fábio Perez, Cristina Vasconcelos, Sandra Avila +1

Deep learning models show remarkable results in automated skin lesion analysis. However, these models demand considerable amounts of data, while the availability of annotated skin…