Artificial generation of populations for machine learning classifiers training to glaucoma diagnosis support (Geração de populações artificiais para treinamento de classificadores de apoio ao diagnóstico de glaucoma). - Marcelo Dias (2009)

How Musical Selection Impacts the Performance of the Interaction with the Computer. - Mickael da Costa; Davide Carneiro; Marcelo Dias; Paulo Novais (IDC, 2014)

Detecção semi-supervisionada de posicionamento em tweets baseada em regras de sentimento. - Marcelo Dias; Karin Becker (SBBD, 2016)

INF-UFRGS-OPINION-MINING at SemEval-2016 Task 6: Automatic Generation of a Training Corpus for Unsupervised Identification of Stance in Tweets. - Marcelo Dias; Karin Becker (SemEval@NAACL-HLT, 2016)

An Heuristics-Based, Weakly-Supervised Approach for Classification of Stance in Tweets. - Marcelo Dias; Karin Becker (WI, 2016)

INF-UFRGS at SemEval-2017 Task 5: A Supervised Identification of Sentiment Score in Tweets and Headlines. - Tiago Zini; Karin Becker; Marcelo Dias (SemEval@ACL, 2017)

Assessing the combination of DistilBERT news representations and difusion topological features to classify fake news. - Carlos Abel Córdova Sáenz; Marcelo Dias; Karin Becker (J. Inf. Data Manag., 2021)

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)