47 citations · 73 across the 7 of their papers we have counts for
9 papers
Mitigating Bias in Facial Analysis Systems by Incorporating Label Diversity
Camila Kolling, Victor Araujo, Adriano Veloso +1
Facial analysis models are increasingly applied in real-world applications that have significant impact on peoples' lives. However, as literature has shown, models that automatical…
Modeling Pharmacological Effects with Multi-Relation Unsupervised Graph Embedding
Dehua Chen, Amir Jalilifard, Adriano Veloso +1
A pharmacological effect of a drug on cells, organs and systems refers to the specific biochemical interaction produced by a drug substance, which is called its mechanism of action…
Explainable Deep CNNs for MRI-Based Diagnosis of Alzheimer's Disease
Eduardo Nigri, Nivio Ziviani, Fabio Cappabianco +2
Deep Convolutional Neural Networks (CNNs) are becoming prominent models for semi-automated diagnosis of Alzheimer's Disease (AD) using brain Magnetic Resonance Imaging (MRI). Altho…
Assessing the Reliability of Visual Explanations of Deep Models with Adversarial Perturbations
Dan Valle, Tiago Pimentel, Adriano Veloso
The interest in complex deep neural networks for computer vision applications is increasing. This leads to the need for improving the interpretable capabilities of these models. Re…
Automatic Tag Recommendation for Painting Artworks Using Diachronic Descriptions
Gianlucca Zuin, Adriano Veloso, João Cândido Portinari +1
In this paper, we deal with the problem of automatic tag recommendation for painting artworks. Diachronic descriptions containing deviations on the vocabulary used to describe each…
Learning Transferable Features for Speech Emotion Recognition
Alison Marczewski, Adriano Veloso, Nívio Ziviani
Emotion recognition from speech is one of the key steps towards emotional intelligence in advanced human-machine interaction. Identifying emotions in human speech requires learning…
Dynamic Prediction of ICU Mortality Risk Using Domain Adaptation
Tiago Alves, Alberto Laender, Adriano Veloso +1
Early recognition of risky trajectories during an Intensive Care Unit (ICU) stay is one of the key steps towards improving patient survival. Learning trajectories from physiologica…
Deep Active Learning for Anomaly Detection
Tiago Pimentel, Marianne Monteiro, Adriano Veloso +1
Anomalies are intuitively easy for human experts to understand, but they are hard to define mathematically. Therefore, in order to have performance guarantees in unsupervised anoma…
Setting Players' Behaviors in World of Warcraft through Semi-Supervised Learning
Marcelo Souza Nery, Roque Anderson Teixeira, Victor do Nascimento Silva +1
Digital games are one of the major and most important fields on the entertainment domain, which also involves cinema and music. Numerous attempts have been done to improve the qual…