His primary scientific interests are in Artificial intelligence, Machine learning, Pattern recognition, Classifier and Deep learning. Raw data is closely connected to Identification in his research, which is encompassed under the umbrella topic of Artificial intelligence. His Machine learning study incorporates themes from Image, Robustness and Pattern recognition.
His studies in Pattern recognition integrate themes in fields like Supervised learning and Connectivity. His Classifier research incorporates elements of Contextual image classification, Algorithm, Data mining and Binary number. In general Deep learning, his work in Boltzmann machine is often linked to Oesophageal adenocarcinoma linking many areas of study.
His scientific interests lie mostly in Artificial intelligence, Machine learning, Classifier, Pattern recognition and Support vector machine. Artificial intelligence is frequently linked to Data mining in his study. His Data mining research is multidisciplinary, incorporating elements of Harmony search and Cluster analysis.
As part of the same scientific family, he usually focuses on Machine learning, concentrating on Metaheuristic and intersecting with Particle swarm optimization. João Paulo Papa studied Pattern recognition and Biometrics that intersect with Spoofing attack. His research in Deep learning intersects with topics in Binary image and Convolutional neural network.
His primary areas of investigation include Artificial intelligence, Machine learning, Deep learning, Pattern recognition and Artificial neural network. Robustness, Convolutional neural network, Contextual image classification, Feature extraction and Support vector machine are among the areas of Artificial intelligence where João Paulo Papa concentrates his study. His Machine learning research incorporates themes from Classifier, Task and Range.
His Classifier research includes elements of Handwriting and Medical diagnosis. João Paulo Papa has researched Pattern recognition in several fields, including Speedup and Identification. His Artificial neural network research includes themes of Isolation and Risk analysis.
His main research concerns Artificial intelligence, Machine learning, Deep learning, Artificial neural network and Feature extraction. His research integrates issues of Field and Pattern recognition in his study of Artificial intelligence. His Machine learning research integrates issues from Classifier, Textual information and Finite element method.
The Classifier study combines topics in areas such as Training set, Basis function, Probabilistic logic, Fuzzy logic and Supervised learning. His work deals with themes such as F1 score, Binary image, Robustness and Hyperparameter, which intersect with Deep learning. His Support vector machine study integrates concerns from other disciplines, such as Unsupervised learning, Cluster analysis and Feature vector.
This overview was generated by a machine learning system which analysed the scientist’s body of work. If you have any feedback, you can contact us here.
Supervised pattern classification based on optimum-path forest
J. P. Papa;A. X. Falcão;C. T. N. Suzuki.
International Journal of Imaging Systems and Technology (2009)
BBA: A Binary Bat Algorithm for Feature Selection
R. Y. M. Nakamura;L. A. M. Pereira;K. A. Costa;D. Rodrigues.
brazilian symposium on computer graphics and image processing (2012)
Efficient supervised optimum-path forest classification for large datasets
JoãO P. Papa;Alexandre X. FalcãO;Victor Hugo C. De Albuquerque;JoãO Manuel R. S. Tavares.
Pattern Recognition (2012)
A genetic programming framework for content-based image retrieval
Ricardo da S. Torres;Alexandre X. Falcão;Marcos A. Gonçalves;João P. Papa.
Pattern Recognition (2009)
A wrapper approach for feature selection based on Bat Algorithm and Optimum-Path Forest
Douglas Rodrigues;Luís A. M. Pereira;Rodrigo Y. M. Nakamura;Kelton A. P. Costa.
Expert Systems With Applications (2014)
Computational methods for the image segmentation of pigmented skin lesions
Roberta B. Oliveira;Mercedes E. Filho;Zhen Ma;João P. Papa.
Computer Methods and Programs in Biomedicine (2016)
BCS: A Binary Cuckoo Search algorithm for feature selection
D. Rodrigues;L. A. M. Pereira;T. N. S. Almeida;J. P. Papa.
international symposium on circuits and systems (2013)
A novel algorithm for feature selection using Harmony Search and its application for non-technical losses detection
Caio C. O. Ramos;André N. Souza;Giovani Chiachia;Alexandre X. Falcão.
Computers & Electrical Engineering (2011)
ECG arrhythmia classification based on optimum-path forest
Eduardo José Da S. Luz;Thiago M. Nunes;Victor Hugo C. De Albuquerque;JoãO P. Papa.
Expert Systems With Applications (2013)
A New Approach for Nontechnical Losses Detection Based on Optimum-Path Forest
C C O Ramos;A N de Sousa;J P Papa;Alexandre Xavier Falcão.
IEEE Transactions on Power Systems (2011)
Profile was last updated on December 6th, 2021.
Research.com Ranking is based on data retrieved from the Microsoft Academic Graph (MAG).
The ranking h-index is inferred from publications deemed to belong to the considered discipline.
If you think any of the details on this page are incorrect, let us know.
We appreciate your kind effort to assist us to improve this page, it would be helpful providing us with as much detail as possible in the text box below: