P. T. Saito

发表

Active Learning with Interactive Response Time and its Application to the Diagnosis of Parasites

A. Falcão, P. T. Saito, P. J. Rezende, 2015 .

Classification of Skin Lesion through Active Learning Strategies.

P. T. Saito, Lucas G. Batista, P. Bugatti, 2022, Computer methods and programs in biomedicine.

Robust active learning for the diagnosis of parasites

Pedro Jussieu de Rezende, Alexandre X. Falcão, Priscila T. M. Saito, 2015, Pattern Recognit..

Content-based image retrieval towards the automatic characterization of soybean seed vigor

Pedro Henrique Bugatti, Priscila T. M. Saito, Marcus G. F. Santanna, 2014, SAC.

Active Semi-supervised Learning Using Optimum-Path Forest

Pedro Jussieu de Rezende, Alexandre X. Falcão, Willian Paraguassu Amorim, 2014, 2014 22nd International Conference on Pattern Recognition.

Pattern recognition analysis on long noncoding RNAs: a tool for prediction in plants

Priscila Tiemi Maeda Saito, Pedro Henrique Bugatti, Wonder Alexandre Luz Alves, 2019, Briefings Bioinform..

TERL: Classification of Transposable Elements by Convolutional Neural Networks

Priscila Tiemi Maeda Saito, Pedro Henrique Bugatti, Alexandre Rossi Paschoal, 2020, bioRxiv.

TERL: Classification of Transposable Elements by Convolutional Neural Networks

Priscila Tiemi Maeda Saito, Pedro Henrique Bugatti, Alexandre Rossi Paschoal, 2020, bioRxiv.

Active semi-supervised learning for biological data classification

Guilherme Camargo, Pedro H Bugatti, Priscila T M Saito, 2020, PloS one.

Towards an Effective and Efficient Learning for Biomedical Data Classification

Priscila Tiemi Maeda Saito, Pedro Henrique Bugatti, Guilherme Camargo, 2017, 2017 IEEE 30th International Symposium on Computer-Based Medical Systems (CBMS).

An Intelligent System to Enhance the Productivity and Sustainability in Soybean Crop Enterprises

Fabrício Martins Lopes, Pedro Henrique Bugatti, Priscila T. M. Saito, 2019, SBSI.

Breast cancer diagnosis through active learning in content-based image retrieval

Pedro H. Bugatti, Priscila T. M. Saito, Rafael S. Bressan, 2019, Neurocomputing.

Pedestrian traffic lights and crosswalk identification

S. R. R. Sanches, P. T. Saito, P. Bugatti, 2022, Multimedia Tools and Applications.

Contributing to agriculture by using soybean seed data from the tetrazolium test

Pedro H. Bugatti, Douglas F. Pereira, Fabricio M. Lopes, 2019, Data in brief.

DeepCloud: An Investigation of Geostationary Satellite Imagery Frame Interpolation for Improved Temporal Resolution

Priscila Tiemi Maeda Saito, Pedro Henrique Bugatti, Luigi Freitas Cruz, 2020, ICAISC.

DROP: A Data Reduction and Organization Paradigm and its Application in Image Analysis

Priscila T. M. Saito, P. T. Saito, 2015 .

An active learning paradigm based on a priori data reduction and organization

Pedro Jussieu de Rezende, Alexandre X. Falcão, Priscila T. M. Saito, 2014, Expert Syst. Appl..

Classification of texture based on Bag-of-Visual-Words through complex networks

Fabrício Martins Lopes, Geovana V. L. de Lima, Priscila T. M. Saito, 2019, Expert Syst. Appl..

Classification of Transposable Elements by Convolutional Neural Networks

Pedro Henrique Bugatti, Priscila T. M. Saito, Alexandre Rossi Paschoal, 2019, ICAISC.

A Complex Network-Based Approach to the Analysis and Classification of Images

Fabrício Martins Lopes, Pedro Henrique Bugatti, Geovana V. L. de Lima, 2015, CIARP.

Method for selecting representative videos for change detection datasets

S. R. R. Sanches, P. T. Saito, P. Bugatti, 2021, Multimedia Tools and Applications.

A Novel Framework for Content-Based Image Retrieval Through Relevance Feedback Optimization

Pedro Henrique Bugatti, Priscila T. M. Saito, Reginaldo Rocha, 2015, CIARP.

Exploring Active Learning Based on Representativeness and Uncertainty for Biomedical Data Classification

Priscila Tiemi Maeda Saito, Pedro Henrique Bugatti, Guilherme Camargo, 2019, IEEE Journal of Biomedical and Health Informatics.

Towards Practical Computer Vision in Teaching and Learning of Image Processing Theories

Pedro H. Bugatti, Priscila T. M. Saito, Lucas de O. Alves, 2019, 2019 IEEE Frontiers in Education Conference (FIE).

Evaluation of Change Detection Algorithms using Difficulty Maps

S. R. R. Sanches, C. G. Corrêa, P. T. Saito, 2023, IEEE Latin America Transactions.

Choosing the Most Effective Pattern Classification Model under Learning-Time Constraint

Alexandre X. Falcão, Rodrigo Y. M. Nakamura, Priscila T. M. Saito, 2015, PloS one.

Assessment of clustering techniques to support the analyses of soybean seed vigor

P. T. Saito, P. Bugatti, E. R. de Oliveira, 2023, PloS one.

Optimum-path forest and active learning approaches for content-based medical image retrieval

P. T. Saito, P. Bugatti, R. S. Bressan, 2022, Optimum-Path Forest.

DeepMammo: Deep Transfer Learning for Lesion Classification of Mammographic Images

Pedro Henrique Bugatti, Priscila T. M. Saito, Daniel H. A. Alves, 2019, 2019 IEEE 32nd International Symposium on Computer-Based Medical Systems (CBMS).

DOCToR: The Role of Deep Features in Content-Based Mammographic Image Retrieval

Pedro Henrique Bugatti, Rafael Staiger Bressan, Priscila T. M. Saito, 2018, 2018 IEEE 31st International Symposium on Computer-Based Medical Systems (CBMS).

Soybean seed vigor classification through an effective image learning-based approach

P. T. Saito, P. H. Bugatti, Marcelo Souza, 2023, Multim. Tools Appl..

Computational Analysis of Transposable Elements and CircRNAs in Plants.

Fabricio M. Lopes, L. S. Oliveira, A. Durham, 2021, Methods in molecular biology.