Google
Google Scholar
Semantic Scholar
MS Academic
CiteSeerX
ORCIDJoão Paulo Papa
João P. Papa
Refine list
refinements active!
zoomed in on ?? of ?? records
view refined list in
export refined list as
showing all ?? records
2020 – today
- 2021
[c132]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- [c131]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 - [i20]Gustavo Henrique de Rosa, Mateus Roder, João P. Papa:
Fast Ensemble Learning Using Adversarially-Generated Restricted Boltzmann Machines. CoRR abs/2101.01042 (2021) - [i19]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) - [i18]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) - [i17]Leandro Aparecido Passos, João Paulo Papa:
A Metaheuristic-Driven Approach to Fine-Tune Deep Boltzmann Machines. CoRR abs/2101.05795 (2021) - [i16]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) - [i15]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) - [i14]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) - [i13]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) - [i12]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) - [i11]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) - [i10]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) - 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): 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): 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) - [c130]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 - [c129]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 - [c128]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 - [c127]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 - [c126]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 - [c125]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 - [c124]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 - [c123]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 - [c122]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 - [c121]Vicente Coelho Lobo Neto, Leandro Aparecido Passos, João Paulo Papa:
Evolving Long Short-Term Memory Networks. ICCS (2) 2020: 337-350 - [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]Luis 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]Silas Evandro Nachif Fernandes, João Paulo Papa:
Improving optimum-path forest learning using bag-of-classifiers and confidence measures. Pattern Anal. Appl. 22(2): 703-716 (2019) - [j66]Willian Paraguassu Amorim, Gustavo Henrique Rosa, Rogério Thomazella, José Eduardo Cogo Castanho, Fábio Romano Lofrano Dotto, Oswaldo Pons Rodrigues Júnior, Aparecido Nilceu Marana, João Paulo Papa:
Semi-supervised learning with connectivity-driven convolutional neural networks. Pattern Recognit. Lett. 128: 16-22 (2019) - [j65]Silas Evandro Nachif Fernandes, Danillo Roberto Pereira, Caio C. O. Ramos, André N. de Souza, Danilo S. Gastaldello, João P. Papa:
A Probabilistic Optimum-Path Forest Classifier for Non-Technical Losses Detection. IEEE Trans. Smart Grid 10(3): 3226-3235 (2019) - [c115]Leandro Aparecido Passos, Douglas Rodrigues, João Paulo Papa:
Quaternion-Based Backtracking Search Optimization Algorithm. CEC 2019: 3014-3021 - [c114]Claudio Filipi Goncalves dos Santos, Thierry Pinheiro Moreira, Danilo Colombo, João Paulo Papa:
Does Pooling Really Matter? An Evaluation on Gait Recognition. CIARP 2019: 751-760 - [c113]Rafael Goncalves Pires, Daniel Felipe Silva Santos, Gustavo Botelho de Souza, Alexandre L. M. Levada, João Paulo Papa:
A Sparse Filtering-Based Approach for Non-blind Deep Image Denoising. ICANN (Workshop) 2019: 471-482 - [c112]Luis Claudio Sugi Afonso, Danilo Colombo, Clayton R. Pereira, Kelton A. P. Costa, João P. Papa:
Multiple-Instance Learning through Optimum-Path Forest. IJCNN 2019: 1-7 - [c111]Leandro Aparecido Passos, Marcos Cleison Silva Santana, Thierry Pinheiro Moreira, João Paulo Papa:
κ-Entropy Based Restricted Boltzmann Machines. IJCNN 2019: 1-8 - [c110]Daniel F. S. Santos, Rafael Goncalves Pires, Danilo Colombo, João P. Papa:
Video Segmentation Learning Using Cascade Residual Convolutional Neural Network. SIBGRAPI 2019: 1-7 - [i6]Gustavo Henrique de Rosa, João P. Papa:
Opytimizer: A Nature-Inspired Python Optimizer. CoRR abs/1912.13002 (2019) - 2018
- [j64]Zaid Abdi Alkareem Alyasseri, Ahamad Tajudin Khader, Mohammed Azmi Al-Betar, João Paulo Papa, Osama Ahmad Alomari:
EEG Feature Extraction for Person Identification Using Wavelet Decomposition and Multi-Objective Flower Pollination Algorithm. IEEE Access 6: 76007-76024 (2018) - [j63]Clayton R. Pereira, Danilo R. Pereira, Gustavo H. Rosa, Victor Hugo C. de Albuquerque, Silke A. T. Weber, Christian Hook, João P. Papa:
Handwritten dynamics assessment through convolutional neural networks: An application to Parkinson's disease identification. Artif. Intell. Medicine 87: 67-77 (2018) - [j62]Luis Antonio De Souza, Christoph Palm, Robert Mendel, Christian Hook, Alanna Ebigbo, Andreas Probst, Helmut Messmann, Silke A. T. Weber, João P. Papa:
A survey on Barrett's esophagus analysis using machine learning. Comput. Biol. Medicine 96: 203-213 (2018) - [j61]Danillo Roberto Pereira, João Paulo Papa, Gustavo Francisco Rosalin Saraiva, Gustavo Maia Souza:
Automatic classification of plant electrophysiological responses to environmental stimuli using machine learning and interval arithmetic. Comput. Electron. Agric. 145: 35-42 (2018) - [j60]João P. Papa, Gustavo H. Rosa, André N. de Souza, Luis Claudio Sugi Afonso:
Feature selection through binary brain storm optimization. Comput. Electr. Eng. 72: 468-481 (2018) - [j59]Eduardo Cabal-Yepez, Guillermo Botella, Amir Hooshang Mazinan, João P. Papa:
Introduction to the special section on Image and Video Processing. Comput. Electr. Eng. 72: 1037-1041 (2018) - [j58]Gustavo Carneiro, João Manuel R. S. Tavares, Andrew P. Bradley, João Paulo Papa, Jacinto C. Nascimento, Jaime S. Cardoso, Zhi Lu, Vasileios Belagiannis:
1st MICCAI workshop on deep learning in medical image analysis. Comput. methods Biomech. Biomed. Eng. Imaging Vis. 6(3): 241-242 (2018) - [j57]Luiz Souza, Luciano Oliveira, Mauricio Pamplona, João P. Papa:
How far did we get in face spoofing detection? Eng. Appl. Artif. Intell. 72: 368-381 (2018) - [j56]Luis Claudio Sugi Afonso, Mateus Basso, Michelle Kuroda, Alexandre Campane Vidal, João P. Papa:
A fast approach for unsupervised karst feature identification using GPU. Comput. Geosci. 119: 1-8 (2018) - [j55]Willian Paraguassu Amorim, Alexandre X. Falcão, João P. Papa:
Multi-label semi-supervised classification through optimum-path forest. Inf. Sci. 465: 86-104 (2018) - [j54]Roberta B. Oliveira, João P. Papa, Aledir Silveira Pereira, João Manuel R. S. Tavares:
Computational methods for pigmented skin lesion classification in images: review and future trends. Neural Comput. Appl. 29(3): 613-636 (2018) - [j53]Victor Hugo C. de Albuquerque, Thiago M. Nunes, Danillo Roberto Pereira, Eduardo José da S. Luz, David Menotti, João P. Papa, João Manuel R. S. Tavares:
Robust automated cardiac arrhythmia detection in ECG beat signals. Neural Comput. Appl. 29(3): 679-693 (2018) - [j52]Leandro Aparecido Passos, João Paulo Papa:
Temperature-Based Deep Boltzmann Machines. Neural Process. Lett. 48(1): 95-107 (2018) - [j51]Gustavo H. Rosa, João P. Papa, Xin-She Yang:
Handling dropout probability estimation in convolution neural networks using meta-heuristics. Soft Comput. 22(18): 6147-6156 (2018) - [j50]Caio C. O. Ramos, Douglas Rodrigues, André N. de Souza, João Paulo Papa:
On the Study of Commercial Losses in Brazil: A Binary Black Hole Algorithm for Theft Characterization. IEEE Trans. Smart Grid 9(2): 676-683 (2018) - [c109]Gustavo Botelho de Souza, Daniel Felipe Silva Santos, Rafael Goncalves Pires, João Paulo Papa, Aparecido Nilceu Marana:
Efficient Width-Extended Convolutional Neural Network for Robust Face Spoofing Detection. BRACIS 2018: 230-235 - [c108]Zaid Abdi Alkareem Alyasseri, Ahamad Tajudin Khader, Mohammed Azmi Al-Betar, João P. Papa, Osama Ahmad Alomari:
EEG-based Person Authentication Using Multi-objective Flower Pollination Algorithm. CEC 2018: 1-8 - [c107]Luis Claudio Sugi Afonso, Daniel Carlos Guimarães Pedronette, André N. de Souza, João Paulo Papa:
Improving Optimum- Path Forest Classification Using Unsupervised Manifold Learning. ICPR 2018: 560-565 - [c106]Danillo Roberto Pereira, João P. Papa, Luciene P. Papa, Rodrigo Jose Pisani:
Land-Use Classification using Finite Element Machines. IGARSS 2018: 7316-7319 - [c105]Rogério Thomazella, José E. C. Castanho, Fébio R. L. Dotto, Oswaldo Pons Rodrigues Júnior, Gustavo Henrique Rosa, Aparecido Nilceu Marana, João P. Papa:
Environmental Monitoring Using Drone Images and Convolutional Neural Networks. IGARSS 2018: 8941-8944 - [c104]Danillo Roberto Pereira, Pedro Pedrosa Rebouças Filho, Gustavo Henrique de Rosa, João Paulo Papa, Victor Hugo C. de Albuquerque:
Stroke Lesion Detection Using Convolutional Neural Networks. IJCNN 2018: 1-6 - [c103]Gustavo José de Sousa, Daniel Carlos Guimarães Pedronette, Alexandro Baldassin, P. I. M. Privatto, M. Gaseta, Ivan Rizzo Guilherme, Danilo Colombo, Luis Claudio Sugi Afonso, João P. Papa:
Pattern Analysis in Drilling Reports using Optimum-Path Forest. IJCNN 2018: 1-8 - [c102]Luis Claudio Sugi Afonso, Leandro A. Passos, João Paulo Papa:
Enhancing Brain Storm Optimization Through Optimum-Path Forest. SACI 2018: 183-188 - [c101]Luiz Fernandoda Silva Cieslak, Kelton Augusto Pontara da Costa, João Paulo Papa:
Seam Carving Detection Using Convolutional Neural Networks. SACI 2018: 195-200 - [c100]Leandro A. Passos, Clayton R. Pereira, Edmar R. S. Rezende, Tiago J. Carvalho, Silke A. T. Weber, Christian Hook, João P. Papa:
Parkinson Disease Identification Using Residual Networks and Optimum-Path Forest. SACI 2018: 325-330 - [c99]Leandro A. Passos, Douglas R. Rodrigues, João P. Papa:
Fine Tuning Deep Boltzmann Machines Through Meta-Heuristic Approaches. SACI 2018: 419-424 - [c98]Luiz Carlos Felix Ribeiro, João Paulo Papa:
Unsupervised Dialogue Act Classification with Optimum-Path Forest. SIBGRAPI 2018: 25-32 - [c97]Luis Souza, Alanna Ebigbo, Andreas Probst, Helmut Messmann, João Paulo Papa, Robert Mendel, Christoph Palm:
Barrett's Esophagus Identification Using Color Co-Occurrence Matrices. SIBGRAPI 2018: 166-173 - [c96]Gustavo Botelho de Souza, João Paulo Papa, Aparecido Nilceu Marana:
On the Learning of Deep Local Features for Robust Face Spoofing Detection. SIBGRAPI 2018: 258-265 - [e3]Danail Stoyanov, Zeike Taylor, Gustavo Carneiro, Tanveer F. Syeda-Mahmood, Anne L. Martel, Lena Maier-Hein, João Manuel R. S. Tavares, Andrew P. Bradley, João Paulo Papa, Vasileios Belagiannis, Jacinto C. Nascimento, Zhi Lu, Sailesh Conjeti, Mehdi Moradi, Hayit Greenspan, Anant Madabhushi:
Deep Learning in Medical Image Analysis - and - Multimodal Learning for Clinical Decision Support - 4th International Workshop, DLMIA 2018, and 8th International Workshop, ML-CDS 2018, Held in Conjunction with MICCAI 2018, Granada, Spain, September 20, 2018, Proceedings. Lecture Notes in Computer Science 11045, Springer 2018, ISBN 978-3-030-00888-8 [contents] - [i5]Gustavo Botelho de Souza, João Paulo Papa, Aparecido Nilceu Marana:
On the Learning of Deep Local Features for Robust Face Spoofing Detection. CoRR abs/1806.07492 (2018) - 2017
- [j49]João Paulo Papa, Gustavo H. Rosa, Danillo Roberto Pereira, Xin-She Yang:
Quaternion-based Deep Belief Networks fine-tuning. Appl. Soft Comput. 60: 328-335 (2017) - [j48]Eduardo Cabal-Yepez, Guillermo Botella, Amir Hooshang Mazinan, João Paulo Papa:
Introduction to the special section on Image and Video Processing. Comput. Electr. Eng. 62: 64-67 (2017) - [j47]Douglas Rodrigues, João P. Papa, Hojjat Adeli:
Meta-heuristic multi- and many-objective optimization techniques for solution of machine learning problems. Expert Syst. J. Knowl. Eng. 34(6) (2017) - [j46]Samuel Luz Gomes, Elizângela de S. Rebouças, Edson Cavalcanti Neto, João P. Papa, Victor Hugo C. de Albuquerque, Pedro Pedrosa Rebouças Filho, João Manuel R. S. Tavares:
Embedded real-time speed limit sign recognition using image processing and machine learning techniques. Neural Comput. Appl. 28(S-1): 573-584 (2017) - [j45]João Paulo Papa, Ryan Farrell:
Editorial: Special Section on deep image and video understanding. Pattern Recognit. 61: 537-538 (2017) - [j44]João Paulo Papa, Silas Evandro Nachif Fernandes, Alexandre Xavier Falcão:
Optimum-Path Forest based on k-connectivity: Theory and applications. Pattern Recognit. Lett. 87: 117-126 (2017) - [j43]João Paulo Papa, Gustavo Henrique Rosa, Luciene P. Papa:
A binary-constrained Geometric Semantic Genetic Programming for feature selection purposes. Pattern Recognit. Lett. 100: 59-66 (2017) - [j42]Danillo Roberto Pereira, Rodrigo Jose Pisani, André N. de Souza, João P. Papa:
An Ensemble-Based Stacked Sequential Learning Algorithm for Remote Sensing Imagery Classification. IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens. 10(4): 1525-1541 (2017) - [j41]Gustavo Botelho de Souza, Daniel Felipe Silva Santos, Rafael Goncalves Pires, Aparecido Nilceu Marana, João Paulo Papa:
Deep Texture Features for Robust Face Spoofing Detection. IEEE Trans. Circuits Syst. II Express Briefs 64-II(12): 1397-1401 (2017) - [c95]Luis Souza, Christian Hook, João Paulo Papa, Christoph Palm:
Barrett's Esophagus Analysis Using SURF Features. Bildverarbeitung für die Medizin 2017: 141-146 - [c94]Gustavo H. Rosa, Luis Claudio Sugi Afonso, Alexandro Baldassin, João P. Papa, Xin-She Yang:
Quaternionic Flower Pollination Algorithm. CAIP (2) 2017: 47-58 - [c93]Clayton R. Pereira, Leandro A. Passos, Ricardo R. Lopes, Silke A. T. Weber, Christian Hook, João Paulo Papa:
Parkinson's Disease Identification Using Restricted Boltzmann Machines. CAIP (2) 2017: 70-80 - [c92]