45 citations · 71 across the 9 of their papers we have counts for
6 papers · 1 filter
Extractive Text Summarization Using Generalized Additive Models with Interactions for Sentence Selection
Vinícius Camargo da Silva, João Paulo Papa, Kelton Augusto Pontara da Costa
Automatic Text Summarization (ATS) is becoming relevant with the growth of textual data; however, with the popularization of public large-scale datasets, some recent machine learni…
From Actions to Events: A Transfer Learning Approach Using Improved Deep Belief Networks
Mateus Roder, Jurandy Almeida, Gustavo H. de Rosa +3
In the last decade, exponential data growth supplied machine learning-based algorithms' capacity and enabled their usage in daily-life activities. Additionally, such an improvement…
Mixup-based Deep Metric Learning Approaches for Incomplete Supervision
Luiz H. Buris, Daniel C. G. Pedronette, Joao P. Papa +3
Deep learning architectures have achieved promising results in different areas (e.g., medicine, agriculture, and security). However, using those powerful techniques in many real ap…
MaxDropoutV2: An Improved Method to Drop out Neurons in Convolutional Neural Networks
Claudio Filipi Goncalves do Santos, Mateus Roder, Leandro A. Passos +1
In the last decade, exponential data growth supplied the machine learning-based algorithms' capacity and enabled their usage in daily life activities. Additionally, such an improve…
Robust deep learning for eye fundus images: Bridging real and synthetic data for enhancing generalization
Guilherme C. Oliveira, Gustavo H. Rosa, Daniel C. G. Pedronette +4
Deep learning applications for assessing medical images are limited because the datasets are often small and imbalanced. The use of synthetic data has been proposed in the literatu…
Multimodal Audio-Visual Information Fusion using Canonical-Correlated Graph Neural Network for Energy-Efficient Speech Enhancement
Leandro Aparecido Passos, João Paulo Papa, Javier Del Ser +2
This paper proposes a novel multimodal self-supervised architecture for energy-efficient audio-visual (AV) speech enhancement that integrates Graph Neural Networks with canonical c…