Optimization of the Fused-DenseNet-Tiny Model Applied to the Detection of COVID-19 and Pneumonia in Chest X-Ray Images - Santos Júnior, Eder Silva dos; Mafalda, Salomão Machado; Chavez, Roger Fredy Larico; Alvarez, Ana Beatriz (Anais do Seminário Integrado de Software e Hardware (SEMISH); 2023: Anais do L Seminário Integrado de Software e Hardware, 2023)
The COVID-19 pandemic, faced in recent years, has highlighted the need for new forms of testing that help in the early diagnosis of the disease. An alternative gaining more and more prominence is the use of Artificial Neural Networks, algorithms capable of being trained to identify this and other diseases. However, these architectures have a high demand for hardware resources, making their implementation difficult. In this work, we propose the optimization of the Fused-DenseNet-Tiny Convolutional Neural Network for the detection of COVID-19 and Pneumonia in x-ray images, using the pruning technique. After pruning, a model with a size about 3 times smaller and an accuracy of 97.17% was obtained, without significant loss.