| Computer-assisted Parkinson's disease diagnosis using fuzzy optimum-path forest and Restricted Boltzmann Machines RWR de Souza, DS Silva, LA Passos, M Roder, MC Santana, PR Pinheiro, ... Computers in Biology and Medicine 131, 104260, 2021 | 38 | 2021 |
| Gait recognition based on deep learning: a survey CFG Santos, DDS Oliveira, LA Passos, RG Pires, DFS Santos, LP Valem, ... arXiv preprint arXiv:2201.03323, 2022 | 34 | 2022 |
| Gait recognition based on deep learning: a survey C Filipi Gonçalves dos Santos, DS Oliveira, L A. Passos, ... ACM Computing Surveys (CSUR) 55 (2), 1-34, 2022 | 19 | 2022 |
| Reinforcing learning in Deep Belief Networks through nature-inspired optimization M Roder, LA Passos, GH de Rosa, VHC de Albuquerque, JP Papa Applied Soft Computing 108, 107466, 2021 | 17 | 2021 |
| MaxDropout: deep neural network regularization based on maximum output values CFG do Santos, D Colombo, M Roder, JP Papa 2020 25th International Conference on Pattern Recognition (ICPR), 2671-2676, 2021 | 12 | 2021 |
| Intestinal parasites classification using deep belief networks M Roder, LA Passos, LCF Ribeiro, BC Benato, AX Falcão, JP Papa International Conference on Artificial Intelligence and Soft Computing, 242-251, 2020 | 12 | 2020 |
| Enhancing anomaly detection through restricted Boltzmann machine features projection GH Rosa, M Roder, DFS Santos, KAP Costa International Journal of Information Technology 13, 49-57, 2021 | 11 | 2021 |
| Learnergy: Energy-based machine learners M Roder, GH de Rosa, JP Papa arXiv preprint arXiv:2003.07443, 2020 | 6 | 2020 |
| Energy-based dropout in restricted Boltzmann machines: why not go random M Roder, GH de Rosa, VHC de Albuquerque, ALD Rossi, JP Papa IEEE Transactions on Emerging Topics in Computational Intelligence 6 (2 …, 2020 | 5 | 2020 |
| Harnessing particle swarm optimization through relativistic velocity M Roder, GH De Rosa, LA Passos, JP Papa, ALD Rossi 2020 IEEE Congress on Evolutionary Computation (CEC), 1-8, 2020 | 4 | 2020 |
| From actions to events: A transfer learning approach using improved deep belief networks M Roder, J Almeida, GH De Rosa, LA Passos, ALD Rossi, JP Papa 2021 IEEE Symposium Series on Computational Intelligence (SSCI), 01-08, 2021 | 3 | 2021 |
| Enhancing shallow neural networks through fourier-based information fusion for stroke classification M Roder, GH Rosa, JP Papa, DCG Pedronette 2021 34th SIBGRAPI Conference on Graphics, Patterns and Images (SIBGRAPI …, 2021 | 3 | 2021 |
| Facial point graphs for amyotrophic lateral sclerosis identification NB Gomes, A Yoshida, M Roder, GC de Oliveira, JP Papa arXiv preprint arXiv:2307.12159, 2023 | 2 | 2023 |
| Neighbour‐based bag‐of‐samplings for person identification through handwritten dynamics and convolutional neural networks GH de Rosa, M Roder, JP Papa Expert Systems 39 (4), e12891, 2022 | 2 | 2022 |
| MaxDropoutV2: An Improved Method to Drop Out Neurons in Convolutional Neural Networks CFG Santos, M Roder, LA Passos, JP Papa Iberian Conference on Pattern Recognition and Image Analysis, 271-282, 2022 | 2 | 2022 |
| Detecting atherosclerotic plaque calcifications of the carotid artery through optimum-path forest DS Jodas, M Roder, R Pires, MCS Santana, LA de Souza Jr, LA Passos Optimum-Path Forest, 137-154, 2022 | 2 | 2022 |
| Improving pre-trained weights through meta-heuristics fine-tuning GH De Rosa, M Roder, JP Papa, CFG Dos Santos 2021 IEEE Symposium Series on Computational Intelligence (SSCI), 1-8, 2021 | 2 | 2021 |
| A layer-wise information reinforcement approach to improve learning in deep belief networks M Roder, LA Passos, LCF Ribeiro, C Pereira, JP Papa International Conference on Artificial Intelligence and Soft Computing, 231-241, 2020 | 2 | 2020 |
| On the assessment of nature-inspired meta-heuristic optimization techniques to fine-tune deep belief networks LA Passos, GH Rosa, D Rodrigues, M Roder, JP Papa Deep Neural Evolution: Deep Learning with Evolutionary Computation, 67-96, 2020 | 2 | 2020 |
| Facial Point Graphs for Stroke Identification NB Gomes, A Yoshida, GC de Oliveira, M Roder, JP Papa Iberoamerican Congress on Pattern Recognition, 685-699, 2023 | 1 | 2023 |
João Paulo PapaFull Professor, IEEE Senior, Alexander von Humboldt Research Fellow, São Paulo State UniversityE-mail confirmado em unesp.br
