Bakhtawar Aslam1, Ziyad Awadh Alrowaili2, Bushra Khaliq1, Jaweria Manzoor1, Saira Raqeeb1, Fahad Ahmad3,*
CMC-Computers, Materials & Continua, Vol.68, No.2, pp. 2159-2178, 2021, DOI:10.32604/cmc.2021.015922
Abstract The concept of classification through deep learning is to build a model that skillfully separates closely-related images dataset into different classes because of diminutive but continuous variations that took place in physical systems over time and effect substantially. This study has made ozone depletion identification through classification using Faster Region-Based Convolutional Neural Network (F-RCNN). The main advantage of F-RCNN is to accumulate the bounding boxes on images to differentiate the depleted and non-depleted regions. Furthermore, image classification’s primary goal is to accurately predict each minutely varied case’s targeted classes in the dataset based on ozone saturation. The permanent changes in… More >
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