74 citations · 131 across the 8 of their papers we have counts for
9 papers
SPACE: Semantic Projection and Alignment of CLIP Embeddings for Domain Adaptation
João Renato Ribeiro Manesco, Danilo Samuel Jodas, Douglas Rodrigues +2
A fundamental challenge in deploying vision models is domain shift, which arises when training and test data follow different distributions, leading to degraded performance. This c…
PUBO Formulation for MST and Application to Optimum-Path Forest
Guilherme E. L. Pexe, Lucas A. M. Rattighieri, Leandro A. Passos +5
The Optimum-Path Forest is a graph-based framework for designing classifiers that exploit inter-sample connectivity. A particular variant constructs decision boundaries based on pr…
FALQON-MST: A Fully Quantum Framework for Graph Optimization in Vision Systems
Guilherme E. L. Pexe, Lucas A. M. Rattighieri, Leandro A. Passos +4
Finding the minimum spanning tree (MST) of a graph is an important task in computer vision, as it enables a sparse and low-cost representation of connectivity among elements (such…
BioNeRF: Biologically Plausible Neural Radiance Fields for View Synthesis
Leandro A. Passos, Douglas Rodrigues, Danilo Jodas +3
This paper presents BioNeRF, a biologically plausible architecture that models scenes in a 3D representation and synthesizes new views through radiance fields. Since NeRF relies on…
Introducing Bode: A Fine-Tuned Large Language Model for Portuguese Prompt-Based Task
Gabriel Lino Garcia, Pedro Henrique Paiola, Luis Henrique Morelli +7
Large Language Models (LLMs) are increasingly bringing advances to Natural Language Processing. However, low-resource languages, those lacking extensive prominence in datasets for…
PL-kNN: A Parameterless Nearest Neighbors Classifier
Danilo Samuel Jodas, Leandro Aparecido Passos, Ahsan Adeel +1
Demands for minimum parameter setup in machine learning models are desirable to avoid time-consuming optimization processes. The -Nearest Neighbors is one of the most effective…
Handling Imbalanced Datasets Through Optimum-Path Forest
Leandro Aparecido Passos, Danilo S. Jodas, Luiz C. F. Ribeiro +3
In the last decade, machine learning-based approaches became capable of performing a wide range of complex tasks sometimes better than humans, demanding a fraction of the time. Suc…
A Review of Deep Learning-based Approaches for Deepfake Content Detection
Leandro A. Passos, Danilo Jodas, Kelton A. P. da Costa +5
Recent advancements in deep learning generative models have raised concerns as they can create highly convincing counterfeit images and videos. This poses a threat to people's inte…
PF: Oversampling via Optimum-Path Forest for Breast Cancer Detection
Leandro Aparecido Passos, Danilo Samuel Jodas, Luiz C. F. Ribeiro +2
Breast cancer is among the most deadly diseases, distressing mostly women worldwide. Although traditional methods for detection have presented themselves as valid for the task, the…