Development of new methodologies and machine intelligence-based technological solutions for digital image segmentation and COVID-19 pandemic response

• Grant number: 21/03328-3
• Support Opportunities: Regular Research Grants
• Duration: August 01, 2021 - July 31, 2023
• Field of knowledge: Physical Sciences and Mathematics - Computer Science - Computing Methodologies and Techniques
• Principal Investigator: Wallace Correa de Oliveira Casaca
• Grantee: Wallace Correa de Oliveira Casaca
• Host Institution: Instituto de Biociências, Letras e Ciências Exatas (IBILCE). Universidade Estadual Paulista (UNESP). Campus de São José do Rio Preto. São José do Rio Preto , SP, Brazil

Abstract

This project comprises two distinct research branches: Digital Image Segmentation and Data-Driven Epidemiological Modeling against COVID-19. Our proposal aims at combining theoretical as well as technical advancements as a solution for different applications in the field of Computational Intelligence, whose previous results have been published in high-quality refereed publications such as IEEE CVPR, IEEE TIP and IEEE TPAMI. Considering the image segmentation topic, new concepts and clustering strategies for graphs derived from digital images will be investigated. Also, techniques inspired on spectral cutting and energy minimization rules will be studied, as well as deep learning strategies and graph differential operators in the image processing context, including eigenvalues and eigenfunctions, thus allowing us to design new methodologies and theoretical results. Concerning the Covid-19 research, this proposal extends the ongoing actions and researches now being carried out against the new coronavirus in Brazil, which range from digital inclusion of the Brazilian society to new studies of mathematical models for forecasting coronavirus-related data in the country. (AU)

Scientific publications

(15)

(References retrieved automatically from Web of Science and SciELO through information on FAPESP grants and their corresponding numbers as mentioned in the publications by the authors)

LUZ, ANDREA ELIZA O.; NEGRI, ROGERIO G.; MASSI, KLECIA G.; COLNAGO, MARILAINE; SILVA, ERIVALDO A.; CASACA, WALLACE. Mapping Fire Susceptibility in the Brazilian Amazon Forests Using Multitemporal Remote Sensing and Time-Varying Unsupervised Anomaly Detection. REMOTE SENSING, v. 14, n. 10, p. 17-pg., 2022-05-01. (21/03328-3, 21/01305-6)

DIAS, MAURICIO ARAUJO; MARINHO, GIOVANNA CARREIRA; NEGRI, ROGERIO GALANTE; CASACA, WALLACE; MUNOZ, IGNACIO BRAVO; ELER, DANILO MEDEIROS. A Machine Learning Strategy Based on Kittler's Taxonomy to Detect Anomalies and Recognize Contexts Applied to Monitor Water Bodies in Environments. REMOTE SENSING, v. 14, n. 9, p. 38-pg., 2022-05-01. (20/06477-7, 21/01305-6, 16/24185-8, 21/03328-3)

MARINHO, GIOVANNA CARREIRA; MARCILIO JUNIOR, WILSON ESTECIO; DIAS, MAURICIO ARAUJO; ELER, DANILO MEDEIROS; NEGRI, ROGERIO GALANTE; CASACA, WALLACE. Dimensionality Reduction and Anomaly Detection Based on Kittler's Taxonomy: Analyzing Water Bodies in Two Dimensional Spaces. REMOTE SENSING, v. 15, n. 16, p. 24-pg., 2023-08-01. (16/24185-8, 21/03328-3, 20/06477-7, 21/01305-6)

BENVENUTO, GIOVANA AUGUSTA; COLNAGO, MARILAINE; CASACA, WALLACE; IEEE. UNSUPERVISED DEEP LEARNING NETWORK FOR DEFORMABLE FUNDUS IMAGE REGISTRATION. 2022 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH AND SIGNAL PROCESSING (ICASSP), v. N/A, p. 5-pg., 2022-01-01. (13/07375-0, 19/26288-7, 21/03328-3)

ANANIAS, PEDRO HENRIQUE M.; NEGRI, ROGERIO G.; DIAS, MAURICIO A.; SILVA, ERIVALDO A.; CASACA, WALLACE. A Fully Unsupervised Machine Learning Framework for Algal Bloom Forecasting in Inland Waters Using MODIS Time Series and Climatic Products. REMOTE SENSING, v. 14, n. 17, p. 22-pg., 2022-09-01. (21/03328-3, 21/01305-6, 16/24185-8)

GINO, VINICIUS L. S.; NEGRI, ROGERIO G.; SOUZA, FELIPE N.; SILVA, ERIVALDO A.; BRESSANE, ADRIANO; MENDES, TATIANA S. G.; CASACA, WALLACE. Integrating Unsupervised Machine Intelligence and Anomaly Detection for Spatio-Temporal Dynamic Mapping Using Remote Sensing Image Series. SUSTAINABILITY, v. 15, n. 6, p. 19-pg., 2023-03-01. (21/03328-3, 21/01305-6)

NEGRI, ROGERIO G.; LUZ, ANDREA E. O.; FRERY, ALEJANDRO C.; CASACA, WALLACE; IEEE. Fire Detection with Multitemporal Multispectral Data and a Probabilistic Unsupervised Technique. 2023 INTERNATIONAL CONFERENCE ON MACHINE INTELLIGENCE FOR GEOANALYTICS AND REMOTE SENSING, MIGARS, v. N/A, p. 4-pg., 2023-01-01. (21/03328-3, 21/01305-6)

BENVENUTO, GIOVANA A.; COLNAGO, MARILAINE; DIAS, MAURICIO A.; NEGRI, ROGERIO G.; SILVA, ERIVALDO A.; CASACA, WALLACE. A Fully Unsupervised Deep Learning Framework for Non-Rigid Fundus Image Registration. BIOENGINEERING-BASEL, v. 9, n. 8, p. 17-pg., 2022-08-01. (13/07375-0, 21/01305-6, 19/26288-7, 21/03328-3)

PARRA, LARISSA M. P.; SANTOS, FABRICIA C.; NEGRI, ROGERIO G.; COLNAGO, MARILAINE; BRESSANE, ADRIANO; DIAS, MAURICIO A.; CASACA, WALLACE. Assessing the impacts of catastrophic 2020 wildfires in the Brazilian Pantanal using MODIS data and Google Earth Engine: A case study in the world's largest sanctuary for Jaguars. EARTH SCIENCE INFORMATICS, v. N/A, p. 11-pg., 2023-08-31. (21/03328-3, 16/24185-8, 21/01305-6)

COLNAGO, MARILAINE; BENVENUTO, GIOVANA A.; CASACA, WALLACE; NEGRI, ROGERIO G.; FERNANDES, EDER G.; CUMINATO, JOSE A.. Risk Factors Associated with Mortality in Hospitalized Patients with COVID-19 during the Omicron Wave in Brazil. BIOENGINEERING-BASEL, v. 9, n. 10, p. 11-pg., 2022-10-01. (21/03328-3, 13/07375-0, 21/01305-6)

BRUZADIN, ALDIMIR; BOAVENTURA, MAURILIO; COLNAGO, MARILAINE; NEGRI, ROGERIO GALANTE; CASACA, WALLACE. Learning label diffusion maps for semi-automatic segmentation of lung CT images with COVID-19. Neurocomputing, v. 522, p. 15-pg., 2023-02-14. (21/03328-3, 13/07375-0, 21/01305-6)

AMARAL, FABIO; CASACA, WALLACE; OISHI, CASSIO M.; CUMINATO, JOSE A.. Simulating Immunization Campaigns and Vaccine Protection Against COVID-19 Pandemic in Brazil. IEEE ACCESS, v. 9, p. 126011-126022, 2021. (21/03328-3, 13/07375-0)

ANANIAS, PEDRO HENRIQUE M.; NEGRI, ROGERIO G.; BRESSANE, ADRIANO; DIAS, MAURICIO A.; SILVA, ERIVALDO A.; CASACA, WALLACE. ABF: A data-driven approach for algal bloom forecasting using machine intelligence and remotely sensed data series. SOFTWARE IMPACTS, v. 17, p. 3-pg., 2023-06-13. (21/03328-3, 16/24185-8, 21/01305-6)

ANANIAS, PEDRO HENRIQUE M.; NEGRI, ROGERIO G.; BRESSANE, ADRIANO; COLNAGO, MARILAINE; CASACA, WALLACE. ABD: A machine intelligent-based algal bloom detector for remote sensing images. SOFTWARE IMPACTS, v. 15, p. 3-pg., 2023-02-17. (21/03328-3, 21/01305-6)

NEGRI, ROGERIO G.; LUZ, ANDREA E. O.; FRERY, ALEJANDRO C.; CASACA, WALLACE. Mapping Burned Areas with Multitemporal-Multispectral Data and Probabilistic Unsupervised Learning. REMOTE SENSING, v. 14, n. 21, p. 20-pg., 2022-11-01. (21/01305-6, 21/03328-3)