4 citations · 7 across the 6 of their papers we have counts for
7 papers
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…
Enhancing Network Intrusion Detection Systems: A Multi-Layer Ensemble Approach to Mitigate Adversarial Attacks
Nasim Soltani, Shayan Nejadshamsi, Zakaria Abou El Houda +4
Adversarial examples can represent a serious threat to machine learning (ML) algorithms. If used to manipulate the behaviour of ML-based Network Intrusion Detection Systems (NIDS),…
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…
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…
FEMa-FS: Finite Element Machines for Feature Selection
Lucas Biaggi, João P. Papa, Kelton A. P Costa +2
Identifying anomalies has become one of the primary strategies towards security and protection procedures in computer networks. In this context, machine learning-based methods emer…
An End-to-End Approach for Seam Carving Detection using Deep Neural Networks
Thierry P. Moreira, Marcos Cleison S. Santana, Leandro A. Passos João Paulo Papa +1
Seam carving is a computational method capable of resizing images for both reduction and expansion based on its content, instead of the image geometry. Although the technique is mo…