FiberNet: A Compact and Efficient Convolutional Neural Network Model for Image Classification - Ferreira, Verner Rafael; Canuto, Anne Magaly de Paula (Anais do Encontro Nacional de Inteligência Artificial e Computacional (ENIAC); 2023: Anais do XX Encontro Nacional de Inteligência Artificial e Computacional, 2023)
Creating a convolutional neural network (CNN) with a minimal number of trainable parameters can offers benefits across diverse application domains. In our paper, presents FiberNet, an efficient CNN model with reduced trainable parameters that guarantees both high accuracy and swift inference. Through empirical analysis confirming its efficacy, the FiberNet model achieved a remarkable 96.25% accuracy on the sisal dataset, 74.90% on the CIFAR10 dataset, and incorporates a total of 754,345 trainable parameters.