A Method Based on Deep Neural Network for Instance Segmentation of Retinal Lesions Caused by Diabetic Retinopathy. - Carlos Santos 007; Marilton S. de Aguiar; Daniel Welfer; Marcelo Silva; Alejandro Pereira; Marcelo Ribeiro; Bruno Belloni (CSCI, 2022)

Detection of retinal microlesions through YOLOR-CSP architecture and image slicing with the SAHI algorithm. - Alejandro Pereira; Carlos Silva 003; Marilton S. de Aguiar; Daniel Welfer; Marcelo Dias; Marcelo Ribeiro; Reza Ahmadi (IJCNN, 2023)

A New Approach for Fundus Lesions Instance Segmentation Based on Mask R-CNN X101-FPN Pre-Trained Architecture. - Carlos Silva 003; Marilton S. de Aguiar; Daniel Welfer; Marcelo Dias; Alejandro Pereira; Marcelo Ribeiro; Bruno Belloni (IEEE Access, 2023)

An Improved Approach for Semantic Segmentation of Fundus Lesions using R2U-Net. - Alejandro Pereira; Carlos Santos 007; Marilton S. de Aguiar; Daniel Welfer; Marcelo Dias; Rafaela de Menezes; Paulo Roberto Ferreira; Fábio D. Rossi; Marcos Cordeiro d'Ornellas; Carlos Jesus Pereira Haygert; Juliano F. Kazienko; Fábio Comim; et al. (EMBC, 2024)

DRAT: A semi-supervised tool for automatic annotation of lesions caused by diabetic retinopathy. - Marcelo Dias; Carlos Santos 007; Marilton S. de Aguiar; Daniel Welfer; Alejandro Pereira; Fernando Ollé (SBSI, 2024)