Recent Submissions

  • A block-based Markov random field model estimation for contextual classification using Optimum-Path Forest

    Osaku, Daniel; Levada, Alexandre L.M.; Papa, Joao Paulo Autor UNESP (Proceedings - IEEE International Symposium on Circuits and Systems, 2016) [Trabalho apresentado em evento]
    Contextual image classification aims at considering the information about nearby samples in the learning process in order to provide more accurate results. In this paper, we propose a locally-adaptive Optimum-Path Forest ...
  • Convolutional neural networks applied for Parkinson’s disease identification

    Pereira, Clayton R.; Pereira, Danillo R. Autor UNESP; Papa, Joao P. Autor UNESP; Rosa, Gustavo H. Autor UNESP; Yang, Xin-She (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2016) [Capítulo de livro]
    Parkinson’s Disease (PD) is a chronic and progressive illness that affects hundreds of thousands of people worldwide. Although it is quite easy to identify someone affected by PD when the illness shows itself (e.g. tremors, ...
  • Preface: DLMIA 2016

    Carneiro, Gustavo; Tavares, João Manuel R.S.; Bradley, Andrew; Papa, João Paulo Autor UNESP; Nascimento, Jacinto C.; Cardoso, Jaime S.; Belagiannis, Vasileios; Lu, Zhi (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2016) [Editorial]
  • A virtual reality environment to support chat rooms for hearing impaired and to teach Brazilian Sign Language (LIBRAS)

    Brega, José Remo Ferreira Autor UNESP; Rodello, Ildeberto Aparecido; Dias, Diego Roberto Colombo; Martins, Valéria Farinazzo; De Paiva Guimarães, Marcelo (Proceedings of IEEE/ACS International Conference on Computer Systems and Applications, AICCSA, 2014) [Trabalho apresentado em evento]
    Improving the way that totally or partially deaf people communicate with the world is a challenging task for our society. One way to improve their communication is to learn sign language, which is a visual language based ...
  • PetroBERT: A Domain Adaptation Language Model for Oil and Gas Applications in Portuguese

    Rodrigues, Rafael B. M. Autor UNESP; Privatto, Pedro I. M. Autor UNESP; de Sousa, Gustavo José Autor UNESP; Murari, Rafael P. Autor UNESP; Afonso, Luis C. S. Autor UNESP; Papa, João P. Autor UNESP; Pedronette, Daniel C. G. Autor UNESP; Guilherme, Ivan R. Autor UNESP; Perrout, Stephan R.; Riente, Aliel F. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2022) [Trabalho apresentado em evento]
    This work proposes the PetroBERT, which is a BERT-based model adapted to the oil and gas exploration domain in Portuguese. PetroBERT was pre-trained using the Petrolês corpus and a private daily drilling report corpus over ...
  • FakeRecogna: A New Brazilian Corpus for Fake News Detection

    Garcia, Gabriel L. Autor UNESP; Afonso, Luis C. S. Autor UNESP; Papa, João P. Autor UNESP (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2022) [Trabalho apresentado em evento]
    Fake news has become a research topic of great importance in Natural Language Processing due to its negative impact on our society. Although its pertinence, there are few datasets available in Brazilian Portuguese and ...
  • Normalizing images is good to improve computer-assisted COVID-19 diagnosis

    Santos, Claudio Filipi Gonçalvesdos; Passos, Leandro Aparecido Autor UNESP; Santana, Marcos Cleisonde Autor UNESP; Papa, João Paulo Autor UNESP (Data Science for COVID-19 Volume 1: Computational Perspectives, 2021) [Capítulo de livro]
    The Coronavirus Disease 2019 (COVID-19) outbreak, caused by the SARS-CoV-2 virus, surprised the whole world in an unprecedented and devastating way, resulting in almost deaths and 2.3 million infections worldwide in less ...
  • EEG Channel Selection Based User Identification via Improved Flower Pollination Algorithm

    Alyasseri, Zaid Abdi Alkareem; Alomari, Osama Ahmad; Papa, João P. Autor UNESP; Al-Betar, Mohammed Azmi; Abdulkareem, Karrar Hameed; Mohammed, Mazin Abed; Kadry, Seifedine; Thinnukool, Orawit; Khuwuthyakorn, Pattaraporn (Sensors, 2022) [Artigo]
    The electroencephalogram (EEG) introduced a massive potential for user identification. Several studies have shown that EEG provides unique features in addition to typical strength for spoofing attacks. EEG provides a graphic ...
  • Improving Pre- Trained Weights through Meta - Heuristics Fine- Tuning

    De Rosa, Gustavo H. Autor UNESP; Roder, Mateus Autor UNESP; Papa, Joao Paulo Autor UNESP; Dos Santos, Claudio F.G. (2021 IEEE Symposium Series on Computational Intelligence, SSCI 2021 - Proceedings, 2021) [Trabalho apresentado em evento]
    Machine Learning algorithms have been extensively researched throughout the last decade, leading to unprecedented advances in a broad range of applications, such as image classification and reconstruction, object recognition, ...
  • From Actions to Events: A Transfer Learning Approach Using Improved Deep Belief Networks

    Roder, Mateus Autor UNESP; Almeida, Jurandy; De Rosa, Gustavo H. Autor UNESP; Passos, Leandro A. Autor UNESP; Rossi, Andre L.D. Autor UNESP; Papa, Joao P. Autor UNESP (2021 IEEE Symposium Series on Computational Intelligence, SSCI 2021 - Proceedings, 2021) [Trabalho apresentado em evento]
    In the last decade, exponential data growth supplied machine learning-based algorithms' capacity and enabled their usage in daily-life activities. Additionally, such an improvement is partially explained due to the advent ...
  • Parallel fuzzy minimals on GPU

    Manacero, Aleardo Autor UNESP; Guariglia, Emanuel Autor UNESP; de Souza, Thiago Alexandre Autor UNESP; Lobato, Renata Spolon Autor UNESP; Spolon, Roberta Autor UNESP (Applied Sciences (Switzerland), 2022) [Artigo]
    Clustering is a classification method that organizes objects into groups based on their similarity. Data clustering can extract valuable information, such as human behavior, trends, and so on, from large datasets by using ...
  • Handling imbalanced datasets through Optimum-Path Forest

    Passos, Leandro Aparecido Autor UNESP; Jodas, Danilo S. Autor UNESP; Ribeiro, Luiz C.F. Autor UNESP; Akio, Marco Autor UNESP; de Souza, Andre Nunes Autor UNESP; Papa, João Paulo Autor UNESP (Knowledge-Based Systems, 2022) [Artigo]
    In the last decade, machine learning-based approaches became capable of performing a wide range of complex tasks sometimes better than humans, demanding a fraction of the time. Such an advance is partially due to the ...
  • KinesiOS: A Telerehabilitation and Functional Analysis System for Post-Stroke Physical Rehabilitation Therapies?

    Scudeletti, Luiz Rogério Autor UNESP; Brandão, Alexandre Fonseca; Dias, Diego Roberto Colombo Autor UNESP; Brega, José Remo Ferreira Autor UNESP (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2021) [Trabalho apresentado em evento]
    The stroke (also known as a Cerebrovascular Accident) is one of the medical conditions that most kills and incapacitates people in the world, affecting men, women and children of many different age brackets. Studies have ...
  • Enhancing Hyper-to-Real Space Projections Through Euclidean Norm Meta-heuristic Optimization

    Ribeiro, Luiz Carlos Felix Autor UNESP; Roder, Mateus Autor UNESP; de Rosa, Gustavo H. Autor UNESP; Passos, Leandro A. Autor UNESP; Papa, João P. Autor UNESP (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2021) [Trabalho apresentado em evento]
    The continuous computational power growth in the last decades has made solving several optimization problems significant to humankind a tractable task; however, tackling some of them remains a challenge due to the overwhelming ...
  • Fine-Tuning Dropout Regularization in Energy-Based Deep Learning

    de Rosa, Gustavo H. Autor UNESP; Roder, Mateus Autor UNESP; Papa, João P. Autor UNESP (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2021) [Trabalho apresentado em evento]
    Deep Learning architectures have been extensively studied in the last years, mainly due to their discriminative power in Computer Vision. However, one problem related to such models concerns their number of parameters and ...
  • Preface

    Tavares, João Manuel R. S.; Papa, João Paulo Autor UNESP; González-Hidalgo, Manuel (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2021) [Editorial]
  • Enhancing Shallow Neural Networks Through Fourier-based Information Fusion for Stroke Classification

    Roder, Mateus Autor UNESP; Rosa, Gustavo Henrique Autor UNESP; Papa, Joao Paulo Autor UNESP; Carlos, Daniel Autor UNESP; Guimaraes, Autor UNESP; Pedronette, Autor UNESP (Proceedings - 2021 34th SIBGRAPI Conference on Graphics, Patterns and Images, SIBGRAPI 2021, 2021) [Trabalho apresentado em evento]
    Deep learning techniques have been widely researched and applied to several problems, ranging from recommendation systems and service-based analysis to medical diagnosis. Nevertheless, even with outstanding results in some ...
  • Improving Transferability of Domain Adaptation Networks Through Domain Alignment Layers

    Silva, Lucas F. A.; Pedronette, Daniel C. G. Autor UNESP; Faria, Fabio A.; Papa, Joao P. Autor UNESP; Almeida, Jurandy (Proceedings - 2021 34th SIBGRAPI Conference on Graphics, Patterns and Images, SIBGRAPI 2021, 2021) [Trabalho apresentado em evento]
    Deep learning (DL) has been the primary approach used in various computer vision tasks due to its relevant results achieved on many tasks. However, on real-world scenarios with partially or no labeled data, DL methods are ...
  • A Deep Learning-based Approach for Tree Trunk Segmentation

    Jodas, Danilo Samuel; Brazolin, Sergio; Yojo, Takashi; De Lima, Reinaldo Araujo; Velasco, Giuliana Del Nero; Machado, Aline Ribeiro; Papa, Joao Paulo Autor UNESP (Proceedings - 2021 34th SIBGRAPI Conference on Graphics, Patterns and Images, SIBGRAPI 2021, 2021) [Trabalho apresentado em evento]
    Recently, the real-time monitoring of the urban ecosystem has raised the attention of many municipal forestry management services. The proper maintenance of trees is seen as crucial to guarantee the quality and safety of ...
  • SMS Spam Detection Through Skip-gram Embeddings and Shallow Networks

    de Sousa, Gustavo José Autor UNESP; Pedronette, Daniel Carlos Guimarães Autor UNESP; Papa, João Paulo Autor UNESP; Guilherme, Ivan Rizzo Autor UNESP (Findings of the Association for Computational Linguistics: ACL-IJCNLP 2021, 2021) [Trabalho apresentado em evento]
    The drastic decrease in mobile SMS costs turned phone users more prone to spam messages, usually with unwanted marketing or questionable content. As such, researchers have proposed different methods for detecting SMS spam ...

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