142 citations · 156 across the 7 of their papers we have counts for
7 papers
A novel YOLO26-MoE optimized by an LLM agent for insulator fault detection considering UAV images
João Pedro Matos-Carvalho, Laio Oriel Seman, Stefano Frizzo Stefenon +2
The inspection of electrical power line insulators is essential for ensuring grid reliability and preventing failures caused by damaged or degraded insulation components. In recent…
EOS-Bench: A Comprehensive Benchmark for Earth Observation Satellite Scheduling
Qian Yin, Jiaxing Li, Jiaqi Cheng +23
Earth observation satellite imaging scheduling is a challenging NP-hard combinatorial optimisation problem central to space mission operations. While next-generation agile Earth ob…
A relax-fix-and-exclude algorithm for an MINLP problem with multilinear interpolations
Bruno Machado Pacheco, Pedro Marcolin Antunes, Eduardo Camponogara +4
This paper introduces a novel algorithm for Mixed-Integer Nonlinear Programming (MINLP) problems with multilinear interpolations of look-up tables. These problems arise when object…
Deep-learning-based Early Fixing for Gas-lifted Oil Production Optimization: Supervised and Weakly-supervised Approaches
Bruno Machado Pacheco, Laio Oriel Seman, Eduardo Camponogara
Maximizing oil production from gas-lifted oil wells entails solving Mixed-Integer Linear Programs (MILPs). As the parameters of the wells, such as the basic-sediment-to-water ratio…
Graph Neural Networks for the Offline Nanosatellite Task Scheduling Problem
Bruno Machado Pacheco, Laio Oriel Seman, Cezar Antonio Rigo +3
This study investigates how to schedule nanosatellite tasks more efficiently using Graph Neural Networks (GNNs). In the Offline Nanosatellite Task Scheduling (ONTS) problem, the go…
Physics-Informed Neural Nets for Control of Dynamical Systems
Eric Aislan Antonelo, Eduardo Camponogara, Laio Oriel Seman +3
Physics-informed neural networks (PINNs) impose known physical laws into the learning of deep neural networks, making sure they respect the physics of the process while decreasing…
Agent-based simulation of the learning dissemination on a Project-Based Learning context considering the human aspects
Laio Oriel Seman, Romeu Hausmann, Eduardo Augusto Bezerra
This work presents an agent-based simulation (ABS) of the active learning process in an Electrical Engineering course. In order to generate input data to the simulation, an active…