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2020 – today
- 2023
[j113]Claudio Filipi Gonçalves dos Santos, Diego de Souza Oliveira, Leandro A. Passos, Rafael Gonçalves Pires, Daniel Felipe Silva Santos, Lucas Pascotti Valem, Thierry Pinheiro Moreira, Marcos Cleison S. Santana, Mateus Roder, João Paulo Papa, Danilo Colombo:
Gait Recognition Based on Deep Learning: A Survey. ACM Comput. Surv. 55(2): 34:1-34:34 (2023)- 2022
- [j112]Zaid Abdi Alkareem Alyasseri
, Osama Ahmad Alomari, Sharif Naser Makhadmeh, Seyedali Mirjalili, Mohammed Azmi Al-Betar, Salwani Abdullah, Nabeel Salih Ali, João P. Papa, Douglas Rodrigues, Ammar Kamal Abasi:
EEG Channel Selection for Person Identification Using Binary Grey Wolf Optimizer. IEEE Access 10: 10500-10513 (2022) - [j111]Gustavo H. de Rosa, Mateus Roder, João P. Papa:
Neighbour-based bag-of-samplings for person identification through handwritten dynamics and convolutional neural networks. Expert Syst. J. Knowl. Eng. 39(4) (2022) - [j110]Danilo Samuel Jodas, Takashi Yojo, Sergio Brazolin, Giuliana Del Nero Velasco, João Paulo Papa:
Detection of Trees on Street-View Images Using a Convolutional Neural Network. Int. J. Neural Syst. 32(1): 2150042:1-2150042:20 (2022) - [j109]Gonzalo Nápoles, Isel Grau, Leonardo Concepción, Lisa Koutsoviti Koumeri, João Paulo Papa:
Modeling implicit bias with fuzzy cognitive maps. Neurocomputing 481: 33-45 (2022) - [j108]Leandro Aparecido Passos, Danilo S. Jodas, Luiz Carlos Felix Ribeiro, Marco Akio, André Nunes de Souza, João Paulo Papa:
Handling imbalanced datasets through Optimum-Path Forest. Knowl. Based Syst. 242: 108445 (2022) - [j107]Zaid Abdi Alkareem Alyasseri, Osama Ahmad Alomari, João P. Papa, Mohammed Azmi Al-Betar, Karrar Hameed Abdulkareem, Mazin Abed Mohammed, Seifedine Kadry, Orawit Thinnukool, Pattaraporn Khuwuthyakorn:
EEG Channel Selection Based User Identification via Improved Flower Pollination Algorithm. Sensors 22(6): 2092 (2022) - [j106]Luiz Carlos Felix Ribeiro, Gustavo H. de Rosa, Douglas Rodrigues, João P. Papa:
Convolutional neural networks ensembles through single-iteration optimization. Soft Comput. 26(8): 3871-3882 (2022) - [j105]Mateus Roder, Gustavo Henrique de Rosa, Victor Hugo C. de Albuquerque, André L. D. Rossi, João P. Papa:
Energy-Based Dropout in Restricted Boltzmann Machines: Why Not Go Random. IEEE Trans. Emerg. Top. Comput. Intell. 6(2): 276-286 (2022) - [c150]Claudio Filipi Goncalves dos Santos, Mateus Roder, Leandro Aparecido Passos, João Paulo Papa:
MaxDropoutV2: An Improved Method to Drop Out Neurons in Convolutional Neural Networks. IbPRIA 2022: 271-282 - [c149]Thierry Pinheiro Moreira, Marcos Cleison S. Santana, Leandro A. Passos, João Paulo Papa, Kelton Augusto Pontara da Costa:
An End-to-End Approach for Seam Carving Detection Using Deep Neural Networks. IbPRIA 2022: 447-457 - [c148]Gabriel L. Garcia, Luis C. S. Afonso, João P. Papa:
FakeRecogna: A New Brazilian Corpus for Fake News Detection. PROPOR 2022: 57-67 - [c147]Rafael Bezerra de Menezes Rodrigues, Pedro Ivo Monteiro Privatto, Gustavo José de Sousa, Rafael P. Murari, Luis C. S. Afonso, João P. Papa, Daniel C. G. Pedronette, Ivan Rizzo Guilherme, Stephan R. Perrout, Aliel F. Riente:
PetroBERT: A Domain Adaptation Language Model for Oil and Gas Applications in Portuguese. PROPOR 2022: 101-109 - [i34]Claudio Filipi Gonçalves dos Santos, João Paulo Papa:
Avoiding Overfitting: A Survey on Regularization Methods for Convolutional Neural Networks. CoRR abs/2201.03299 (2022) - [i33]Claudio Filipi Gonçalves dos Santos, Diego de Souza Oliveira, Leandro A. Passos, Rafael Gonçalves Pires, Daniel Felipe Silva Santos, Lucas Pascotti Valem, Thierry Pinheiro Moreira, Marcos Cleison Silva Santana, Mateus Roder, João Paulo Papa, Danilo Colombo:
Gait Recognition Based on Deep Learning: A Survey. CoRR abs/2201.03323 (2022) - [i32]Gustavo Henrique de Rosa, Mateus Roder, João Paulo Papa:
Comparative Study Between Distance Measures On Supervised Optimum-Path Forest Classification. CoRR abs/2202.03854 (2022) - [i31]Leandro Aparecido Passos, João Paulo Papa, Amir Hussain, Ahsan Adeel:
A Multimodal Canonical-Correlated Graph Neural Network for Energy-Efficient Speech Enhancement. CoRR abs/2202.04528 (2022) - [i30]Leandro A. Passos, Danilo S. Jodas, Kelton A. P. da Costa, Luis Antônio Souza Júnior, Danilo Colombo, João Paulo Papa:
A Review of Deep Learning-based Approaches for Deepfake Content Detection. CoRR abs/2202.06095 (2022) - [i29]Leandro Aparecido Passos, Danilo S. Jodas, Luiz Carlos Felix Ribeiro, Marco Akio, André Nunes de Souza, João Paulo Papa:
Handling Imbalanced Datasets Through Optimum-Path Forest. CoRR abs/2202.08934 (2022) - [i28]Thierry Pinheiro Moreira, Marcos Cleison S. Santana, Leandro Aparecido Passos, João Paulo Papa, Kelton Augusto Pontara da Costa:
An End-to-End Approach for Seam Carving Detection using Deep Neural Networks. CoRR abs/2203.02728 (2022) - [i27]Claudio Filipi Goncalves dos Santos, Mateus Roder, Leandro A. Passos, João P. Papa:
MaxDropoutV2: An Improved Method to Drop out Neurons in Convolutional Neural Networks. CoRR abs/2203.02740 (2022) - [i26]Guilherme C. Oliveira, Gustavo H. Rosa, Daniel C. G. Pedronette, João P. Papa, Himeesh Kumar, Leandro A. Passos, Dinesh Kant Kumar:
Which Generative Adversarial Network Yields High-Quality Synthetic Medical Images: Investigation Using AMD Image Datasets. CoRR abs/2203.13856 (2022) - [i25]Renato William R. de Souza, João Vitor Chaves de Oliveira, Leandro A. Passos, Weiping Ding, João P. Papa, Victor Hugo C. de Albuquerque:
A Novel Approach for Optimum-Path Forest Classification Using Fuzzy Logic. CoRR abs/2204.06635 (2022) - [i24]Luiz H. Buris, Daniel C. G. Pedronette, João P. Papa, Jurandy Almeida, Gustavo Carneiro, Fábio Augusto Faria:
Mixup-based Deep Metric Learning Approaches for Incomplete Supervision. CoRR abs/2204.13572 (2022) - 2021
- [j104]Mateus Roder, Leandro Aparecido Passos, Gustavo Henrique de Rosa, Victor Hugo C. de Albuquerque, João Paulo Papa:
Reinforcing learning in Deep Belief Networks through nature-inspired optimization. Appl. Soft Comput. 108: 107466 (2021) - [j103]Luis Antônio de Souza Junior, Robert Mendel, Sophia Strasser, Alanna Ebigbo, Andreas Probst, Helmut Messmann, João P. Papa, Christoph Palm:
Convolutional Neural Networks for the evaluation of cancer in Barrett's esophagus: Explainable AI to lighten up the black-box. Comput. Biol. Medicine 135: 104578 (2021) - [j102]Danilo Tedesco, Bruno Rafael de Almeida Moreira, Marcelo Rodrigues Barbosa Júnior, João Paulo Papa, Rouverson Pereira da Silva:
Predicting on multi-target regression for the yield of sweet potato by the market class of its roots upon vegetation indices. Comput. Electron. Agric. 191: 106544 (2021) - [j101]Adriana S. Iwashita, Douglas Rodrigues, Danilo S. Gastaldello, André Nunes de Souza, João Paulo Papa:
An incremental Optimum-Path Forest classifier and its application to non-technical losses identification. Comput. Electr. Eng. 95: 107389 (2021) - [j100]Gustavo Henrique de Rosa, João P. Papa:
A survey on text generation using generative adversarial networks. Pattern Recognit. 119: 108098 (2021) - [j99]Gustavo Henrique de Rosa, João P. Papa:
OPFython: A Python implementation for Optimum-Path Forest. Softw. Impacts 9: 100113 (2021) - [c146]Gustavo José de Sousa, Daniel Carlos Guimarães Pedronette, João Paulo Papa, Ivan Rizzo Guilherme:
SMS Spam Detection Through Skip-gram Embeddings and Shallow Networks. ACL/IJCNLP (Findings) 2021: 4193-4201 - [c145]Robert Mendel, Luis Antônio de Souza Junior, David Rauber, João Paulo Papa, Christoph Palm:
Abstract: Semi-supervised Segmentation Based on Error-correcting Supervision. Bildverarbeitung für die Medizin 2021: 178 - [c144]Luis Antonio De Souza, Leandro A. Passos, Robert Mendel, Alanna Ebigbo, Andreas Probst, Helmut Messmann, Christoph Palm, João Paulo Papa:
Fine-tuning Generative Adversarial Networks using Metaheuristics - A Case Study on Barrett's Esophagus Identification. Bildverarbeitung für die Medizin 2021: 205-210 - [c143]Gustavo Henrique de Rosa, Mateus Roder, João P. Papa:
Fine-Tuning Dropout Regularization in Energy-Based Deep Learning. CIARP 2021: 99-108 - [c142]Luiz Carlos Felix Ribeiro, Mateus Roder, Gustavo Henrique de Rosa, Leandro A. Passos, João P. Papa:
Enhancing Hyper-to-Real Space Projections Through Euclidean Norm Meta-heuristic Optimization. CIARP 2021: 109-118 - [c141]Daniel F. S. Santos, Rafael Goncalves Pires, Leandro A. Passos, João P. Papa:
DDIPNet and DDIPNet+: Discriminant Deep Image Prior Networks for Remote Sensing Image Classification. IGARSS 2021: 2843-2846 - [c140]Rafael Goncalves Pires, Daniel F. S. Santos, Leandro A. Passos, João P. Papa:
Deep Regressor Networks for Blind Image Deblurring. IGARSS 2021: 5390-5393 - [c139]Lucas Fernando Alvarenga e Silva, Daniel C. G. Pedronette, Fábio Augusto Faria, João P. Papa, Jurandy Almeida:
Improving Transferability of Domain Adaptation Networks Through Domain Alignment Layers. SIBGRAPI 2021: 168-175 - [c138]Danilo Samuel Jodas, Sergio Brazolin, Takashi Yojo, Reinaldo Araujo de Lima, Giuliana Del Nero Velasco, Aline Ribeiro Machado, João Paulo Papa:
A Deep Learning-based Approach for Tree Trunk Segmentation. SIBGRAPI 2021: 370-377 - [c137]Mateus Roder, Gustavo Henrique Rosa, João Paulo Papa, Daniel Carlos Guimarães Pedronette:
Enhancing Shallow Neural Networks Through Fourier-based Information Fusion for Stroke Classification. SIBGRAPI 2021: 378-385 - [c136]Paulo R. Galego Hernandes, Camila P. Floret, Katia F. Cardozo De Almeida, Vinícius Camargo Da Silva, João Paulo Papa, Kelton Augusto Pontara da Costa:
Phishing Detection Using URL-based XAI Techniques. SSCI 2021: 1-6 - [c135]Mateus Roder, Jurandy Almeida, Gustavo Henrique de Rosa, Leandro A. Passos, André L. D. Rossi, João P. Papa:
From Actions to Events: A Transfer Learning Approach Using Improved Deep Belief Networks. SSCI 2021: 1-8 - [c134]Gustavo Henrique de Rosa, Mateus Roder, João Paulo Papa, Claudio Filipi Goncalves dos Santos:
Improving Pre- Trained Weights through Meta - Heuristics Fine- Tuning. SSCI 2021: 1-8 - [e4]João Manuel R. S. Tavares, João Paulo Papa, Manuel González Hidalgo:
Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications - 25th Iberoamerican Congress, CIARP 2021, Porto, Portugal, May 10-13, 2021, Revised Selected Papers. Lecture Notes in Computer Science 12702, Springer 2021, ISBN 978-3-030-93419-4 [contents] - [i23]Gustavo Henrique de Rosa, Mateus Roder, João P. Papa:
Fast Ensemble Learning Using Adversarially-Generated Restricted Boltzmann Machines. CoRR abs/2101.01042 (2021) - [i22]Gustavo Henrique de Rosa, João Paulo Papa, Xin-She Yang:
A Nature-Inspired Feature Selection Approach based on Hypercomplex Information. CoRR abs/2101.05652 (2021) - [i21]Leandro Aparecido Passos, Danilo Samuel Jodas, Luiz Carlos Felix Ribeiro, Thierry Pinheiro Moreira, João P. Papa:
O2PF: Oversampling via Optimum-Path Forest for Breast Cancer Detection. CoRR abs/2101.05775 (2021) - [i20]Leandro Aparecido Passos, João Paulo Papa:
A Metaheuristic-Driven Approach to Fine-Tune Deep Boltzmann Machines. CoRR abs/2101.05795 (2021) - [i19]Mateus Roder, Gustavo Henrique de Rosa, Victor Hugo C. de Albuquerque, André L. D. Rossi, João P. Papa:
Energy-based Dropout in Restricted Boltzmann Machines: Why not go random. CoRR abs/2101.06741 (2021) - [i18]Mateus Roder, Leandro A. Passos, Luiz Carlos Felix Ribeiro, Barbara Caroline Benato, Alexandre Xavier Falcão, João Paulo Papa:
Intestinal Parasites Classification Using Deep Belief Networks. CoRR abs/2101.06747 (2021) - [i17]Mateus Roder, Leandro A. Passos, Luiz Carlos Felix Ribeiro, Clayton R. Pereira, João Paulo Papa:
A Layer-Wise Information Reinforcement Approach to Improve Learning in Deep Belief Networks. CoRR abs/2101.06749 (2021) - [i16]Luis Antônio de Souza Junior, Luis C. S. Afonso, Alanna Ebigbo, Andreas Probst, Helmut Messmann, Robert Mendel, Christoph Palm, João P. Papa:
Learning Visual Representations with Optimum-Path Forest and its Applications to Barrett's Esophagus and Adenocarcinoma Diagnosis. CoRR abs/2101.07209 (2021) - [i15]Rafael Goncalves Pires, Daniel F. S. Santos, Marcos C. S. Santana, Cláudio F. G. Santos, João Paulo Papa:
Image Denoising using Attention-Residual Convolutional Neural Networks. CoRR abs/2101.07713 (2021) - [i14]Nathalia Q. Ascenção, Luis C. S. Afonso, Danilo Colombo, Luciano Oliveira, João P. Papa:
Information Ranking Using Optimum-Path Forest. CoRR abs/2102.07917 (2021) - [i13]Luis C. S. Afonso, Clayton R. Pereira, Silke A. T. Weber, Christian Hook, Alexandre X. Falcão, João P. Papa:
Hierarchical Learning Using Deep Optimum-Path Forest. CoRR abs/2102.09312 (2021) - [i12]Gustavo Henrique de Rosa, João Paulo Papa:
Speeding Up OPFython with Numba. CoRR abs/2106.11828 (2021) - [i11]Lucas Fernando Alvarenga e Silva, Daniel Carlos Guimarães Pedronette, Fábio Augusto Faria, João Paulo Papa, Jurandy Almeida:
Improving Transferability of Domain Adaptation Networks Through Domain Alignment Layers. CoRR abs/2109.02693 (2021) - [i10]Gonzalo Nápoles, Isel Grau, Leonardo Concepción, Lisa Koutsoviti Koumeri, João Paulo Papa:
Modeling Implicit Bias with Fuzzy Cognitive Maps. CoRR abs/2112.12713 (2021) - 2020
- [j98]Douglas Rodrigues, Victor Hugo C. de Albuquerque, João Paulo Papa:
A multi-objective artificial butterfly optimization approach for feature selection. Appl. Soft Comput. 94: 106442 (2020) - [j97]Gustavo Henrique de Rosa, João P. Papa, Xin-She Yang:
A nature-inspired feature selection approach based on hypercomplex information. Appl. Soft Comput. 94: 106453 (2020) - [j96]Leandro Aparecido Passos, João Paulo Papa:
A metaheuristic-driven approach to fine-tune Deep Boltzmann Machines. Appl. Soft Comput. 97(Part B): 105717 (2020) - [j95]Kelton A. P. da Costa, João P. Papa, Leandro A. Passos, Danilo Colombo, Javier Del Ser, Khan Muhammad, Victor Hugo C. de Albuquerque:
A critical literature survey and prospects on tampering and anomaly detection in image data. Appl. Soft Comput. 97(Part B): 106727 (2020) - [j94]Luis Antônio de Souza Junior, Leandro A. Passos, Robert Mendel, Alanna Ebigbo, Andreas Probst, Helmut Messmann, Christoph Palm, João P. Papa:
Assisting Barrett's esophagus identification using endoscopic data augmentation based on Generative Adversarial Networks. Comput. Biol. Medicine 126: 104029 (2020) - [j93]Gustavo Carneiro, João Manuel R. S. Tavares, Andrew P. Bradley, João Paulo Papa, Vasileios Belagiannis, Jacinto C. Nascimento, Zhi Lu:
Special issue: 4th MICCAI workshop on deep learning in medical image analysis. Comput. methods Biomech. Biomed. Eng. Imaging Vis. 8(5): 501 (2020) - [j92]Guilherme B. Martins, João Paulo Papa, Hojjat Adeli:
Deep learning techniques for recommender systems based on collaborative filtering. Expert Syst. J. Knowl. Eng. 37(6) (2020) - [j91]Marcos C. S. Santana, Leandro Aparecido Passos Júnior, Thierry Pinheiro Moreira, Danilo Colombo, Victor Hugo C. de Albuquerque, João Paulo Papa:
A Novel Siamese-Based Approach for Scene Change Detection With Applications to Obstructed Routes in Hazardous Environments. IEEE Intell. Syst. 35(1): 44-53 (2020) - [j90]Aldo Culquicondor, Alexandro Baldassin, César Castelo-Fernández, João P. L. de Carvalho, João Paulo Papa:
An efficient parallel implementation for training supervised optimum-path forest classifiers. Neurocomputing 393: 259-268 (2020) - [j89]Luis C. S. Afonso, Clayton R. Pereira, Silke A. T. Weber, Christian Hook, Alexandre X. Falcão, João P. Papa:
Hierarchical learning using deep optimum-path forest. J. Vis. Commun. Image Represent. 71: 102823 (2020) - [j88]Guilherme B. Martins, Danillo Roberto Pereira, Jurandy Gomes de Almeida Junior, Victor Hugo C. de Albuquerque, João Paulo Papa:
OPFSumm: on the video summarization using Optimum-Path Forest. Multim. Tools Appl. 79(15-16): 11195-11211 (2020) - [j87]Luis Antonio De Souza, Luis Claudio Sugi Afonso, Alanna Ebigbo, Andreas Probst, Helmut Messmann, Robert Mendel, Christian Hook, Christoph Palm, João P. Papa:
Learning visual representations with optimum-path forest and its applications to Barrett's esophagus and adenocarcinoma diagnosis. Neural Comput. Appl. 32(3): 759-775 (2020) - [j86]Danilo R. Pereira, Marco Antonio Piteri, André N. de Souza, João Paulo Papa, Hojjat Adeli:
FEMa: a finite element machine for fast learning. Neural Comput. Appl. 32(10): 6393-6404 (2020) - [j85]Danilo Colombo, Gilson Brito Alves Lima, Danillo Roberto Pereira, João P. Papa:
Regression-based finite element machines for reliability modeling of downhole safety valves. Reliab. Eng. Syst. Saf. 198: 106894 (2020) - [j84]Claudio Filipi Goncalves dos Santos, Thierry Pinheiro Moreira, Danilo Colombo, João Paulo Papa:
Does Removing Pooling Layers from Convolutional Neural Networks Improve Results? SN Comput. Sci. 1(5): 275 (2020) - [j83]Renato William R. de Souza, João Vitor Chaves de Oliveira, Leandro A. Passos, Weiping Ding, João P. Papa, Victor Hugo C. de Albuquerque:
A Novel Approach for Optimum-Path Forest Classification Using Fuzzy Logic. IEEE Trans. Fuzzy Syst. 28(12): 3076-3086 (2020) - [c133]Henrique Leal Tavares, João Baptista Cardia Neto, João Paulo Papa, Danilo Colombo, Aparecido Nilceu Marana:
People Identification Based on Soft Biometrics Features Obtained from 2D Poses. BRACIS 2020: 318-332 - [c132]Claudio Filipi Goncalves dos Santos, Luis Claudio Sugi Afonso, Clayton Reginaldo Pereira, João Paulo Papa:
BreastNet: Breast Cancer Categorization Using Convolutional Neural Networks. CBMS 2020: 463-468 - [c131]Leandro A. Passos, Danilo S. Jodas, Luiz Carlos Felix Ribeiro, Thierry Pinheiro Moreira, João Paulo Papa:
O^2PF: Oversampling via Optimum-Path Forest for Breast Cancer Detection. CBMS 2020: 498-503 - [c130]Mateus Roder, Gustavo Henrique de Rosa, João Paulo Papa, Fabricio Aparecido Breve:
Fine-Tuning Temperatures in Restricted Boltzmann Machines Using Meta-Heuristic Optimization. CEC 2020: 1-8 - [c129]Mateus Roder, Gustavo Henrique de Rosa, Leandro Aparecido Passos, João Paulo Papa, André Luis Debiaso Rossi:
Harnessing Particle Swarm optimization Through Relativistic Velocity. CEC 2020: 1-8 - [c128]Robert Mendel, Luis Antonio De Souza, David Rauber, João Paulo Papa, Christoph Palm:
Semi-supervised Segmentation Based on Error-Correcting Supervision. ECCV (29) 2020: 141-157 - [c127]Mateus Roder, Leandro A. Passos, Luiz Carlos Felix Ribeiro, Clayton R. Pereira, João Paulo Papa:
A Layer-Wise Information Reinforcement Approach to Improve Learning in Deep Belief Networks. ICAISC (1) 2020: 231-241 - [c126]Mateus Roder, Leandro A. Passos, Luiz Carlos Felix Ribeiro, Barbara Caroline Benato, Alexandre Xavier Falcão, João Paulo Papa:
Intestinal Parasites Classification Using Deep Belief Networks. ICAISC (1) 2020: 242-251 - [c125]Thiago José Lucas, Carlos Alexandre Carvalho Tojeiro, Rafael Goncalves Pires, Kelton Augusto Pontara da Costa, João Paulo Papa:
Machine Learning for Web Intrusion Detection: A Comparative Analysis of Feature Selection Methods mRMR and PFI. ICAISC (1) 2020: 535-546 - [c124]Vicente Coelho Lobo Neto, Leandro Aparecido Passos, João Paulo Papa:
Evolving Long Short-Term Memory Networks. ICCS (2) 2020: 337-350 - [c123]Álvaro R. Ferreira, Gustavo Henrique de Rosa, João P. Papa, Gustavo Carneiro, Fábio Augusto Faria:
Creating Classifier Ensembles through Meta-heuristic Algorithms for Aerial Scene Classification. ICPR 2020: 415-422 - [c122]Claudio Filipi Goncalves dos Santos, Danilo Colombo, Mateus Roder, João Paulo Papa:
MaxDropout: Deep Neural Network Regularization Based on Maximum Output Values. ICPR 2020: 2671-2676 - [c121]João Gabriel Camacho Presotto, Lucas Pascotti Valem, Nikolas Gomes de Sá, Daniel Carlos Guimarães Pedronette, João Paulo Papa:
Weakly Supervised Learning through Rank-based Contextual Measures. ICPR 2020: 5752-5759 - [c120]Nathalia Q. Ascenção, Luis C. S. Afonso, Danilo Colombo, Luciano Oliveira, João P. Papa:
Information Ranking Using Optimum-Path Forest. IJCNN 2020: 1-8 - [c119]Jefferson Fontinele, Marcelo Mendonça, Marco Ruiz, João P. Papa, Luciano Oliveira:
Faster α-expansion via dynamic programming and image partitioning. IJCNN 2020: 1-8 - [c118]Rafael Goncalves Pires, Daniel F. S. Santos, Cláudio F. G. Santos, Marcos C. S. Santana, João P. Papa:
Image Denoising using Attention-Residual Convolutional Neural Networks. SIBGRAPI 2020: 101-107 - [c117]Daniel F. S. Santos, Rafael Goncalves Pires, Danilo Colombo, João P. Papa:
Scene Change Detection Using Multiscale Cascade Residual Convolutional Neural Networks. SIBGRAPI 2020: 108-115 - [c116]Leonardo Tadeu Lopes, Lucas Pascotti Valem, Daniel Carlos Guimarães Pedronette, Ivan Rizzo Guilherme, João Paulo Papa, Marcos Cleison Silva Santana, Danilo Colombo:
Manifold Learning-based Clustering Approach Applied to Anomaly Detection in Surveillance Videos. VISIGRAPP (5: VISAPP) 2020: 404-412 - [p4]Douglas Rodrigues, Gustavo Henrique de Rosa, Leandro Aparecido Passos, João Paulo Papa:
Adaptive Improved Flower Pollination Algorithm for Global Optimization. Nature-Inspired Computation in Data Mining and Machine Learning 2020: 1-21 - [i9]Gustavo Henrique de Rosa, João Paulo Papa, Alexandre Xavier Falcão:
OPFython: A Python-Inspired Optimum-Path Forest Classifier. CoRR abs/2001.10420 (2020) - [i8]Mateus Roder, Gustavo Henrique de Rosa, João Paulo Papa:
Learnergy: Energy-based Machine Learners. CoRR abs/2003.07443 (2020) - [i7]Claudio Filipi Goncalves dos Santos, Danilo Colombo, Mateus Roder, João Paulo Papa:
MaxDropout: Deep Neural Network Regularization Based on Maximum Output Values. CoRR abs/2007.13723 (2020)
2010 – 2019
- 2019
- [j82]Adriana S. Iwashita, João Paulo Papa:
An Overview on Concept Drift Learning. IEEE Access 7: 1532-1547 (2019) - [j81]Clayton R. Pereira, Danilo R. Pereira, Silke A. T. Weber, Christian Hook, Victor Hugo C. de Albuquerque, João P. Papa:
A survey on computer-assisted Parkinson's Disease diagnosis. Artif. Intell. Medicine 95: 48-63 (2019) - [j80]Parham Khojasteh, Leandro A. Passos Junior, Tiago J. Carvalho, Edmar R. S. Rezende, Behzad Aliahmad, João Paulo Papa, Dinesh Kant Kumar:
Exudate detection in fundus images using deeply-learnable features. Comput. Biol. Medicine 104: 62-69 (2019) - [j79]Luiz Carlos Felix Ribeiro, Luis Claudio Sugi Afonso, João P. Papa:
Bag of Samplings for computer-assisted Parkinson's disease diagnosis based on Recurrent Neural Networks. Comput. Biol. Medicine 115 (2019) - [j78]Willian Paraguassu Amorim, Everton Castelao Tetila, Hemerson Pistori, João Paulo Papa:
Semi-supervised learning with convolutional neural networks for UAV images automatic recognition. Comput. Electron. Agric. 164 (2019) - [j77]Gustavo Carneiro, João Manuel R. S. Tavares, Andrew P. Bradley, João Paulo Papa, Jacinto C. Nascimento, Jaime S. Cardoso, Zhi Lu, Vasileios Belagiannis:
Editorial. Comput. methods Biomech. Biomed. Eng. Imaging Vis. 7(3): 241 (2019) - [j76]Kelton A. P. da Costa, João P. Papa, Celso O. Lisboa, Roberto Muñoz, Victor Hugo C. de Albuquerque:
Internet of Things: A survey on machine learning-based intrusion detection approaches. Comput. Networks 151: 147-157 (2019) - [j75]Luis Claudio Sugi Afonso, Gustavo H. Rosa, Clayton R. Pereira, Silke A. T. Weber, Christian Hook, Victor Hugo C. de Albuquerque, João P. Papa:
A recurrence plot-based approach for Parkinson's disease identification. Future Gener. Comput. Syst. 94: 282-292 (2019) - [j74]Adriana S. Iwashita, Victor Hugo C. de Albuquerque, João Paulo Papa:
Learning concept drift with ensembles of optimum-path forest-based classifiers. Future Gener. Comput. Syst. 95: 198-211 (2019) - [j73]Luis Alexandre da Silva, Kelton A. P. da Costa, João P. Papa, Gustavo H. Rosa, Victor Hugo C. de Albuquerque:
Fine-tuning restricted Boltzmann machines using quaternions and its application for spam detection. IET Networks 8(3): 164-168 (2019) - [j72]Gustavo Botelho de Souza, Daniel Felipe Silva Santos, Rafael Goncalves Pires, Aparecido Nilceu Marana, João Paulo Papa:
Deep Features Extraction for Robust Fingerprint Spoofing Attack Detection. J. Artif. Intell. Soft Comput. Res. 9(1): 41-49 (2019) - [j71]Leandro A. Passos, Luis Antônio de Souza Junior, Robert Mendel, Alanna Ebigbo, Andreas Probst, Helmut Messmann, Christoph Palm, João Paulo Papa:
Barrett's esophagus analysis using infinity Restricted Boltzmann Machines. J. Vis. Commun. Image Represent. 59: 475-485 (2019) - [j70]Pedro Pedrosa Rebouças Filho, Antônio Carlos da Silva Barros, Geraldo L. B. Ramalho, Clayton R. Pereira, João Paulo Papa, Victor Hugo C. de Albuquerque, João Manuel R. S. Tavares:
Automated recognition of lung diseases in CT images based on the optimum-path forest classifier. Neural Comput. Appl. 31(S-2): 901-914 (2019) - [j69]Luís A. M. Pereira, João P. Papa, André L. V. Coelho, Clodoaldo Ap. M. Lima, Danillo Roberto Pereira, Victor Hugo C. de Albuquerque:
Automatic identification of epileptic EEG signals through binary magnetic optimization algorithms. Neural Comput. Appl. 31(S-2): 1317-1329 (2019) - [j68]Raniere Rocha Guimarães, Leandro A. Passos, Raimir Holanda Filho, Victor Hugo C. de Albuquerque, Joel J. P. C. Rodrigues, Mikhail M. Komarov, João Paulo Papa:
Intelligent Network Security Monitoring Based on Optimum-Path Forest Clustering. IEEE Netw. 33(2): 126-131 (2019) - [j67]