Recent Submissions

  • Corpus-based Methodology for an Online Multilingual Collocations Dictionary: First Steps

    Orenha-Ottaiano, Adriane Autor UNESP; Garcia, Marcos; de Oliveira Silva, Maria Eugênia Olímpio; L'Homme, Marie-Claude; Ramos, Margarita Alonso; Valêncio, Carlos Roberto Autor UNESP; Tenório, William Autor UNESP (Proceedings of Electronic Lexicography in the 21st Century Conference, 2021) [Trabalho apresentado em evento]
    This paper describes the first steps of a corpus-based methodology for the development of an online Platform for Multilingual Collocations Dictionaries (PLATCOL). The platform is aimed to be customized for different target ...
  • Wavelets behind the scenes: Practical aspects, insights, and perspectives

    Guido, Rodrigo Capobianco Autor UNESP (Physics Reports, 2022) [Resenha]
    Over the years, wavelet-based analyses have been responsible for remarkable achievements in physics and related sciences. Nevertheless, a deep inspection on wavelet-based strategies described in recent scientific papers, ...
  • Interpretability, Reproducibility, and Replicability

    Adali, Tulay; Guido, Rodrigo Capobianco Autor UNESP; Ho, Tin Kam; Muller, Klaus-Robert; Strother, Stephen (IEEE Signal Processing Magazine, 2022) [Editorial]
    Most of the work we do in signal processing these days is data driven. The shift from the more traditional and model-driven approaches to those that are data driven has also underlined the importance of explainability of ...
  • Empirical mode decomposition applied to acoustic detection of a cicadid pest

    Souza, Uender Barbosa de; Escola, João Paulo Lemos; Maccagnan, Douglas Henrique Bottura; Brito, Leonardo da Cunha; Guido, Rodrigo Capobianco Autor UNESP (Computers and Electronics in Agriculture, 2022) [Artigo]
    The sounds emitted by various insect species are highly specific and, thus, can be used as a way to acoustically characterize them. Consequently, acoustic insect detection has been widely studied by the scientific community ...
  • Multidimensional shannon entropy (HM) as an approach to classify H&E colorectal images

    Santos, Luiz Fernando Segato Dos Autor UNESP; Rozendo, Guilherme Botazzo Autor UNESP; Nascimento, Marcelo Zanchetta Do; Tosta, Thaina Aparecida Azevedo; Longo, Leonardo Henrique Da Costa Autor UNESP; Neves, Leandro Alves Autor UNESP (International Conference on Systems, Signals, and Image Processing, 2022) [Trabalho apresentado em evento]
    In this work, we have proposed a method that combines multiscale and multidimensional approaches with Shannon entropy, named HM. The method was combined with other fractal and sample entropy techniques and tested on H&E ...
  • Ensembles of fractal descriptors with multiple deep learned features for classification of histological images

    Da Costa Longo, Leonardo Henrique Autor UNESP; Do Nascimento, Marcelo Zanchetta; Roberto, Guilherme Freire; Martins, Alessandro S.; Dos Santos, Luiz Fernando Segato Autor UNESP; Neves, Leandro Alves Autor UNESP (International Conference on Systems, Signals, and Image Processing, 2022) [Trabalho apresentado em evento]
    In this paper, we propose an approach to study the ensemble of handcrafted and deep learned features, as well as possible templates for associating them for the classification of histological images. The handcrafted features ...
  • Classification of H&E images exploring ensemble learning with two-stage feature selection

    Tenguam, Jaqueline Junko Autor UNESP; Da Costa Longo, Leonardo Henrique Autor UNESP; Silva, Adriano Barbosa; De Faria, Paulo Rogerio; Do Nascimento, Marcelo Zanchetta; Neves, Leandro Alves Autor UNESP (International Conference on Systems, Signals, and Image Processing, 2022) [Trabalho apresentado em evento]
    In this work, an investigation based on ensemble learning is presented for the recognition of patterns in histological tissues stained with Hematoxylin and Eosin, representative of breast cancer, colorectal cancer, liver ...
  • Percolation Features: An approach for evaluating fractal properties in colour images[Formula presented]

    Roberto, Guilherme Freire; Neves, Leandro Alves Autor UNESP; da Costa Longo, Leonardo Henrique Autor UNESP; Rozendo, Guilherme Botazzo Autor UNESP; Tosta, Thaína Aparecida Azevedo; de Faria, Paulo Rogério; Martins, Alessandro Santana; do Nascimento, Marcelo Zanchetta (Software Impacts, 2022) [Artigo]
    Percolation is a physical phenomenon that describes the transport of fluids through porous media. We present a new approach for extracting local and global percolation features from RGB images. The proposed method is based ...
  • Studies about Snake Peptides: A Review about Brazilian Contribution

    Assis, Rhayane Alves Autor UNESP; Bittar, Bruno Barros; Amorim, Nathan Pereira Lima; Carrasco, Guilherme Henrique; Silveira, Elaine Divina Rodrigues; Benvindo-Souza, Marcelino; de Souza Santos, Lia Raquel (Brazilian Archives of Biology and Technology, 2022) [Artigo]
    The peptides present in snake venoms are studied because of their properties, constitutions, mechanisms of action and pharmacological potential. Recognizing this potential, the present study reports the contributions of ...
  • Apriori-roaring: frequent pattern mining method based on compressed bitmaps

    Colombo, Alexandre Autor UNESP; Spolon, Roberta Autor UNESP; Junior, Aleardo Manacero Autor UNESP; Lobato, Renata Spolon Autor UNESP; Cavenaghi, Marcos Antônio (International Journal of Business Intelligence and Data Mining, 2022) [Artigo]
    Association rule mining is one of the most common tasks in data analysis. It has a descriptive feature used to discover patterns in sets of data. Most existing approaches to data analysis have a constraint related to ...
  • Sample Entropy Signatures: A new way to interpret SampEn values[Formula presented]

    Rozendo, Guilherme Botazzo Autor UNESP; do Nascimento, Marcelo Zanchetta; Roberto, Guilherme Freire; de Faria, Paulo Rogério; Silva, Adriano Barbosa; Tosta, Thaína Aparecida Azevedo; Neves, Leandro Alves Autor UNESP (Software Impacts, 2022) [Artigo]
    We present the Sample Entropy Signatures method, which provides a new way to represent images via Sample entropy (SampEn). The proposed method defines texture signatures from multiple SampEn values obtained from combinations ...
  • Classification of non-Hodgkin lymphomas based on sample entropy signatures[Formula presented]

    Rozendo, Guilherme Botazzo Autor UNESP; Nascimento, Marcelo Zanchetta do; Roberto, Guilherme Freire; Faria, Paulo Rogério de; Silva, Adriano Barbosa; Tosta, Thaína Aparecida Azevedo; Neves, Leandro Alves Autor UNESP (Expert Systems with Applications, 2022) [Resenha]
    Computational systems to provide studies and diagnoses of non-Hodgkin's lymphomas have been increasingly developed to assist specialists in their decision-making. On the other hand, the approaches have not yet fully explored ...
  • Early Identification of Abused Domains in TLD through Passive DNS Applying Machine Learning Techniques

    Silva, Leandro Marcos da Autor UNESP; Silveira, Marcos Rogério Autor UNESP; Cansian, Adriano Mauro Autor UNESP; Kobayashi, Hugo Koji (International Journal of Communication Networks and Information Security, 2022) [Artigo]
    DNS is vital for the proper functioning of the Internet. However, users use this structure for domain registration and abuse. These domains are used as tools for these users to carry out the most varied attacks. Thus, early ...
  • Faults in Cloud Environment

    Lobato, Renata Spolon Autor UNESP; Silva, Fabio Amorim da Autor UNESP; Spolon, Roberta Autor UNESP; Manacero Jr, Aleardo Autor UNESP; Tamashiro, Camila Baleiro Okado; Cavenaghi, Marcos Antonio; Rocha, A.; Goncalves, R.; Penalvo, F. G.; Martins, J. (Proceedings Of 2021 16th Iberian Conference On Information Systems And Technologies (cisti'2021), 2021) [Trabalho apresentado em evento]
    Cloud computing is an area in great expansion in the recently years and have begin to be indispensable for greatest majority of world population, even for those who do not work directly on technical areas. One of the ...
  • Explainability of Methods for Critical Information Extraction From Clinical Documents A survey of representative works

    Ho, Tin Kam; Luo, Yen-Fu; Guido, Rodrigo Capobianco Autor UNESP (Ieee Signal Processing Magazine, 2022) [Artigo]
  • Feature Selection with Hybrid Bio-inspired Approach for Classifying Multi-idiom Social Media Sentiment Analysis

    Silva, Luis Marcello Moraes Autor UNESP; Valencio, Carlos Roberto Autor UNESP; Zafalon, Geraldo Francisco Donega Autor UNESP; Columbini, Angelo Cesar; Filipe, J.; Smialek, M.; Brodsky, A.; Hammoudi, S. (Iceis: Proceedings Of The 24th International Conference On Enterprise Information Systems - Vol 1, 2022) [Trabalho apresentado em evento]
    Social media sentiment analysis consists on extracting information from users' comments. It can assist the decision-making process of companies, aid public health and security and even identify intentions and opinions about ...
  • Detection of Newly Registered Malicious Domains through Passive DNS

    Silveira, Marcos Rogerio Autor UNESP; Silva, Leandro Marcos da Autor UNESP; Cansian, Adriano Mauro Autor UNESP; Kobayashi, Hugo Koji; Chen, Y.; Ludwig, H.; Tu, Y.; Fayyad, U.; Zhu, X; Hu, X et al. (2021 Ieee International Conference On Big Data (big Data), 2021) [Trabalho apresentado em evento]
    Due to the importance of DNS for the good functioning of the Internet, malicious users register domains for malicious purposes, such as the spreading of malware and the practice of phishing. In this work, an approach capable ...
  • TRIAD: Whale Optimization Algorithm for 5G-IoT Resource Allocation Decision in Edge Computing

    Lieira, Douglas Dias Autor UNESP; Quessada, Matheus Sanches Autor UNESP; Cristiani, Andre Luis; Immich, Roger; Meneguette, Rodolfo Ipolito; Rocha, A.; Goncalves, R.; Penalvo, F. G.; Martins, J. (Proceedings Of 2021 16th Iberian Conference On Information Systems And Technologies (cisti'2021), 2021) [Trabalho apresentado em evento]
    The massive growth in the number of 5G-IoT devices circulating in the world has increased the demand for computing resources in recent years. That way, it is necessary to search for the development of new solutions or ...
  • Mining negative rules: a literature review focusing on performance

    Colombo, Alexandre Autor UNESP; Spolon, Roberta Autor UNESP; Lobato, Renata Spolon Autor UNESP; Manacero Junior, Aleardo Autor UNESP; Cavenaghi, Marcos Antonio; Rocha, A.; Goncalves, R.; Penalvo, F. G.; Martins, J. (Proceedings Of 2021 16th Iberian Conference On Information Systems And Technologies (cisti'2021), 2021) [Trabalho apresentado em evento]
    Mining of frequent patterns and association rules is a Data Mining task that aims to determine consistent relationships among elements in a transaction database. Algorithms that consider the absence of elements perform the ...
  • Modeling and simulation of tasks interactions using graphical interface

    Peronaglio, Fernando F. Autor UNESP; Manacero, Aleardo Autor UNESP; Lobato, Renata S. Autor UNESP; Spolon, Roberta Autor UNESP; Cavenaghi, Marcos A.; Rocha, A.; Goncalves, R.; Penalvo, F. G.; Martins, J. (Proceedings Of 2021 16th Iberian Conference On Information Systems And Technologies (cisti'2021), 2021) [Trabalho apresentado em evento]
    Concurrent processes are very important to the development of modern applications, where several tasks are performed in order to accomplish a certain activity. Unfortunately, many concurrent applications, including hard ...

View more