activity
20222024
most citedHigh-Order Conditional Mutual Information Maximization for dealing with High-Order Dependencies in Feature Selection

41 citations · 42 across the 6 of their papers we have counts for

collaborators

5 papers

cs.AI20241 cited

Causality from Bottom to Top: A Survey

Abraham Itzhak Weinberg, Cristiano Premebida, Diego Resende Faria

Causality has become a fundamental approach for explaining the relationships between events, phenomena, and outcomes in various fields of study. It has invaded various fields and a…

cs.CV2023

Reducing the False Positive Rate Using Bayesian Inference in Autonomous Driving Perception

Gledson Melotti, Johann J. S. Bastos, Bruno L. S. da Silva +2

Object recognition is a crucial step in perception systems for autonomous and intelligent vehicles, as evidenced by the numerous research works in the topic. In this paper, object…

cs.CV2023

Multispectral Image Segmentation in Agriculture: A Comprehensive Study on Fusion Approaches

Nuno Cunha, Tiago Barros, Mário Reis +3

Multispectral imagery is frequently incorporated into agricultural tasks, providing valuable support for applications such as image segmentation, crop monitoring, field robotics, a…

cs.CV2023

TReR: A Lightweight Transformer Re-Ranking Approach for 3D LiDAR Place Recognition

Tiago Barros, Luís Garrote, Martin Aleksandrov +2

Autonomous driving systems often require reliable loop closure detection to guarantee reduced localization drift. Recently, 3D LiDAR-based localization methods have used retrieval-…

cs.LG202241 cited

High-Order Conditional Mutual Information Maximization for dealing with High-Order Dependencies in Feature Selection

Francisco Souza, Cristiano Premebida, Rui Araújo

This paper presents a novel feature selection method based on the conditional mutual information (CMI). The proposed High Order Conditional Mutual Information Maximization (HOCMIM)…