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Danielle A. Fortunato, Silvia C. Ferreira, Patricia P. F. Ferraz, Rafael A. Santos, and Daniel F. Leite, will present the work “Rede Granular Convolucional Evolutiva para Classificação de Fluxo de Imagens” at the XXV Brazilian Congress of Automation (CBA), which will take place from October 15 to 18, 2024, in Rio de Janeiro, Brazil. This work introduces the Convolutional Evolutive Granular Neural Network (CEGNN), which uses the VGG-16 architecture as a feature extraction base and integrates it with an Evolutive Granular Neural Network (EGNN). This is a new approach to image recognition and classification, combining convolutional neural network techniques with a granular evolutive model. The goal is to advance incremental learning capabilities and improve the interpretability of computer vision models.

The CBA congress is highly significant in the fields of automation and control in Brazil, bringing together experts and researchers to share recent advancements. The acceptance of this paper underscores the importance of the research and offers opportunities for networking and partnerships, particularly with the collaboration of institutions such as Universidade Estadual de Campinas (UNICAMP), Universidade Federal de Lavras (UFLA), and Paderborn University in Germany.