Multi-Objective RSO-Based Convolutional Neural Networks

RSO is used to find the optimal values for the hyperparameters of the deep-learning Architecture

Rat Swarm Optimizer (RSO) is one of the recently published swarm intelligence algorithms proposed in late 2020 by G. Dhiman. This paper introduces a novel diagnosis approach, namely RSO-AlexNet-COVID-19. The proposed hybrid approach is based on the rat swarm optimizer (RSO) and convolutional neural network (CNN). RSO is used to find the optimal values for the hyperparameters of the AlexNet Architecture to achieve a high level of diagnostic accuracy for COVID-19. It obtained overall classification accuracy of 100% for CT images datasets and an accuracy of 95.58% for the X-ray images dataset. Moreover, the performance of the proposed hybrid approach is compared with other CNN architecture, Inception v3, VGG16, and VGG19.