20 citations · 20 across the 6 of their papers we have counts for
6 papers
FairPIVARA: Reducing and Assessing Biases in CLIP-Based Multimodal Models
Diego A. B. Moreira, Alef Iury Ferreira, Jhessica Silva +10
Despite significant advancements and pervasive use of vision-language models, a paucity of studies has addressed their ethical implications. These models typically require extensiv…
Computer Vision Model Compression Techniques for Embedded Systems: A Survey
Alexandre Lopes, Fernando Pereira dos Santos, Diulhio de Oliveira +2
Deep neural networks have consistently represented the state of the art in most computer vision problems. In these scenarios, larger and more complex models have demonstrated super…
CAPIVARA: Cost-Efficient Approach for Improving Multilingual CLIP Performance on Low-Resource Languages
Gabriel Oliveira dos Santos, Diego A. B. Moreira, Alef Iury Ferreira +9
This work introduces CAPIVARA, a cost-efficient framework designed to enhance the performance of multilingual CLIP models in low-resource languages. While CLIP has excelled in zero…
Self-supervised Learning of Contextualized Local Visual Embeddings
Thalles Santos Silva, Helio Pedrini, Adín Ramírez Rivera
We present Contextualized Local Visual Embeddings (CLoVE), a self-supervised convolutional-based method that learns representations suited for dense prediction tasks. CLoVE deviate…
SelfGraphVQA: A Self-Supervised Graph Neural Network for Scene-based Question Answering
Bruno Souza, Marius Aasan, Helio Pedrini +1
The intersection of vision and language is of major interest due to the increased focus on seamless integration between recognition and reasoning. Scene graphs (SGs) have emerged a…
MIA-3DCNN: COVID-19 Detection Based on a 3D CNN
Igor Kenzo Ishikawa Oshiro Nakashima, Giovanna Vendramini, Helio Pedrini
Early and accurate diagnosis of COVID-19 is essential to control the rapid spread of the pandemic and mitigate sequelae in the population. Current diagnostic methods, such as RT-PC…