Hierarchical Cloud Architecture For Identifying The Bite Of “egyptian Cobra” Based On Deep Learning And Quantum Particle Swarm Optimization

This article presents a comparison between cloud and edge computing paradigms, and a deep learning model that is used to identify the Egyptian cobra bite in an accurate manner based on an image of the marks of the bites. The dataset used for the model consists of 500 images of cobra bites marks and 600 images of marks of other species of snakes that exist in Egypt. Data augmentation and transfer learning techniques are used to boost the generalization and accuracy of the model.