Recent Submissions

  • Quaternion-Based Backtracking Search Optimization Algorithm

    Passos, Leandro Aparecido; Rodrigues, Douglas; Papa, Joao Paulo Autor UNESP (2019 IEEE Congress on Evolutionary Computation, CEC 2019 - Proceedings, 2019) [Trabalho apresentado em evento]
    Fitness landscape has been one of the main limitations regarding optimization tasks. Although meta-heuristic techniques have achieved outstanding results over a large variety of problems, some issues related to the function ...
  • Semi-supervised learning with connectivity-driven convolutional neural networks

    Amorim, Willian Paraguassu; Rosa, Gustavo Henrique Autor UNESP; Thomazella, Rogério Autor UNESP; Castanho, José Eduardo Cogo Autor UNESP; Dotto, Fábio Romano Lofrano Autor UNESP; Júnior, Oswaldo Pons Rodrigues; Marana, Aparecido Nilceu Autor UNESP; Papa, João Paulo Autor UNESP (Pattern Recognition Letters, 2019) [Artigo]
    The annotation of large datasets is an issue whose challenge increases as the number of labeled samples available to train the classifier reduces in comparison to the amount of unlabeled data. In this context, semi-supervised ...
  • Fine-tuning restricted Boltzmann machines using quaternions and its application for spam detection

    Da Silva, Luis A. Autor UNESP; Da Costa, Kelton A.P. Autor UNESP; Papa, João P. Autor UNESP; Rosa, Gustavo Autor UNESP; De Albuquerque, Victor Hugo C. (IET Networks, 2019) [Artigo]
    Restricted Boltzmann Machines (RBMs) have been used in a number of applications, but only a few works have addressed them in the context of information security. However, such models have their performance severely affected ...
  • 3D face recognition with reconstructed faces from a collection of 2D images

    Neto, João Baptista Cardia; Marana, Aparecido Nilceu Autor UNESP (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2019) [Trabalho apresentado em evento]
    Nowadays, there is an increasing need for systems that can accurately and quickly identify a person. Traditional identification methods utilize something a person knows or something a person has. This kind of methods has ...
  • FEMa: a finite element machine for fast learning

    Pereira, Danilo R.; Piteri, Marco Antonio Autor UNESP; Souza, André N. Autor UNESP; Papa, João Paulo Autor UNESP; Adeli, Hojjat (Neural Computing and Applications, 2019) [Artigo]
    Machine learning has played an essential role in the past decades and has been in lockstep with the main advances in computer technology. Given the massive amount of data generated daily, there is a need for even faster ...
  • AMFC tool: Auditing and monitoring for cloud computing

    Pauro, Leandro Autor UNESP; Spolon, Roberta Autor UNESP; Bruschi, Gustavo Autor UNESP; Manacero, Aleardo Autor UNESP; Lobato, Renata Autor UNESP; Cavenaghi, Marcos (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2019) [Trabalho apresentado em evento]
    Cloud Computing has been increasingly incorporated by companies as a cost-effective way to make resources and services continuously available. However, as a consequence of service downtimes at cloud providers, achieving ...
  • Spatiotemporal CNNs for pornography detection in videos

    da Silva, Murilo Varges; Marana, Aparecido Nilceu Autor UNESP (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2019) [Trabalho apresentado em evento]
    With the increasing use of social networks and mobile devices, the number of videos posted on the Internet is growing exponentially. Among the inappropriate contents published on the Internet, pornography is one of the ...
  • Use of virtual load curves for the training of neural networks for residential electricity consumption forecasting applications

    Haroldo, L. M. Do Amaral; Souza, Andre N. De Autor UNESP; Gastaldello, Danilo S.; Palma, Thiago X. Da S. Autor UNESP; Maranho, Alexander Da S. Autor UNESP; Papa, Joao P. Autor UNESP (2018 13th IEEE International Conference on Industry Applications, INDUSCON 2018 - Proceedings, 2019) [Trabalho apresentado em evento]
    Smart grids are becoming increasingly closer to consumers, especially residential consumers, bringing with them a wide range of possibilities. The level of information obtained on a smart grid will be much higher when ...
  • Parallelization of the DIANA algorithm in openMP

    Ribeiro, Hethini Autor UNESP; Spolon, Roberta Autor UNESP; Manacero, Aleardo Autor UNESP; Lobato, Renata S. Autor UNESP (Communications in Computer and Information Science, 2019) [Trabalho apresentado em evento]
    Global data production has been increasing by approximately 40% per year since the beginning of the last decade. These large datasets, also called Big Data, are posing great challenges in many areas and in particular in ...
  • On the Learning of Deep Local Features for Robust Face Spoofing Detection

    Botelho De Souza, Gustavo; Papa, João Paulo Autor UNESP; Marana, Aparecido Nilceu Autor UNESP (Proceedings - 31st Conference on Graphics, Patterns and Images, SIBGRAPI 2018, 2019) [Trabalho apresentado em evento]
    Biometrics emerged as a robust solution for security systems. However, given the dissemination of biometric applications, criminals are developing techniques to circumvent them by simulating physical or behavioral traits ...
  • Unsupervised Dialogue Act Classification with Optimum-Path Forest

    Ribeiro, Luiz Carlos Felix Autor UNESP; Papa, João Paulo Autor UNESP (Proceedings - 31st Conference on Graphics, Patterns and Images, SIBGRAPI 2018, 2019) [Trabalho apresentado em evento]
    Dialogue Act classification is a relevant problem for the Natural Language Processing field either as a standalone task or when used as input for downstream applications. Despite its importance, most of the existing ...
  • Barrett's esophagus analysis using infinity Restricted Boltzmann Machines

    Passos, Leandro A.; de Souza, Luis A.; Mendel, Robert; Ebigbo, Alanna; Probst, Andreas; Messmann, Helmut; Palm, Christoph; Papa, João Paulo Autor UNESP (Journal of Visual Communication and Image Representation, 2019) [Artigo]
    The number of patients with Barret's esophagus (BE) has increased in the last decades. Considering the dangerousness of the disease and its evolution to adenocarcinoma, an early diagnosis of BE may provide a high probability ...
  • Efficient width-extended convolutional neural network for robust face spoofing detection

    Botelho De Souza, Gustavo; Da Silva Santos, Daniel Felipe Autor UNESP; Goncalves Pires, Rafael; Papa, Joao Paulo Autor UNESP; Marana, Aparecido Nilceu Autor UNESP (Proceedings - 2018 Brazilian Conference on Intelligent Systems, BRACIS 2018, 2018) [Trabalho apresentado em evento]
    Biometrics has been increasingly used as a safe and convenient technique for people identification. Despite the higher security of biometric systems, criminals have already developed methods to circumvent them, being the ...
  • Learning visual representations with optimum-path forest and its applications to Barrett’s esophagus and adenocarcinoma diagnosis

    de Souza, Luis A.; Afonso, Luis C. S.; Ebigbo, Alanna; Probst, Andreas; Messmann, Helmut; Mendel, Robert; Hook, Christian; Palm, Christoph; Papa, João P. Autor UNESP (Neural Computing and Applications, 2019) [Artigo]
    Considering the increase in the number of the Barrett’s esophagus (BE) in the last decade, and its expected continuous increase, methods that can provide an early diagnosis of dysplasia in BE-diagnosed patients may provide ...
  • Improving Optimum- Path Forest Classification Using Unsupervised Manifold Learning

    Afonso, Luis C. S.; Pedronette, Daniel C. G. Autor UNESP; De Souza, Andre N. Autor UNESP; Papa, Joao P. Autor UNESP (Proceedings - International Conference on Pattern Recognition, 2018) [Trabalho apresentado em evento]
    Appropriate metrics are paramount for machine learning and pattern recognition. In Content-based Image Retrieval-oriented applications, low-level features and pairwise-distance metrics are usually not capable of representing ...
  • An Energy-aware Task Scheduler Based in Ownership Fairness Applied to Federated Grids

    Forte, Cassio H. V. Autor UNESP; Manacero, Aleardo Autor UNESP; Lobato, Renata S. Autor UNESP; Spolon, Roberta Autor UNESP (Proceedings - IEEE Symposium on Computers and Communications, 2018) [Trabalho apresentado em evento]
    The increasing complexity and the large volume of data used by applications lead to an ever-increasing use of high-performance distributed systems. The right management of energy consumption became a major challenge to ...
  • A recurrence plot-based approach for Parkinson's disease identification

    Afonso, Luis C.S.; Rosa, Gustavo H. Autor UNESP; Pereira, Clayton R. Autor UNESP; Weber, Silke A.T. Autor UNESP; Hook, Christian; Albuquerque, Victor Hugo C.; Papa, João P. Autor UNESP (Future Generation Computer Systems, 2019) [Artigo]
    Parkinson's disease (PD) is a neurodegenerative disease that affects millions of people worldwide, causing mental and mainly motor dysfunctions. The negative impact on the patient's daily routine has moved the science in ...
  • Blank spots identification on plantations

    Crulhas, Joao Pedro Rubira Autor UNESP; Artero, Almir Oliveira Autor UNESP; Piteri, Marco Antonio Autor UNESP; Silva, Francisco Assis Da; Pereira, Danillo Roberto; Eler, Danilo Medeiros Autor UNESP; Papa, João Paulo Autor UNESP; De Albuquerque, Victor Hugo C. (IEEE Latin America Transactions, 2018) [Artigo]
    This paper presents a proposal to make the identification of failures in plantations performing an automatic analysis of images collected by the UAVs. What is sought is to identify and measure the areas where the process ...
  • Exudate detection in fundus images using deeply-learnable features

    Khojasteh, Parham; Passos Júnior, Leandro Aparecido; Carvalho, Tiago; Rezende, Edmar; Aliahmad, Behzad; Papa, João Paulo Autor UNESP; Kumar, Dinesh Kant (Computers in Biology and Medicine, 2019) [Artigo]
    Presence of exudates on a retina is an early sign of diabetic retinopathy, and automatic detection of these can improve the diagnosis of the disease. Convolutional Neural Networks (CNNs) have been used for automatic exudate ...
  • Feature selection through binary brain storm optimization

    Papa, João P. Autor UNESP; Rosa, Gustavo H. Autor UNESP; de Souza, André N. Autor UNESP; Afonso, Luis C.S. (Computers and Electrical Engineering, 2018) [Artigo]
    Feature selection stands for the process of finding the most relevant subset of features based on some criterion, which turns out to be an optimization task. In this context, several metaheuristic techniques have been ...

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