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Existing methods for diagnosing leaf disease include statistical approaches, data mining, image processing, machine learning, and deep learning techniques. This review mainly addresses diseases of the rice crop, a framework to diagnose rice crop diseases, and computational approaches in Image Processing, Machine Learning, Deep Learning, and Convolutional Neural Networks. Based on performance indicators, interpretations were made for the following algorithms namely support vector machine (SVM), convolutional neural network (CNN), backpropagational neural network (BPNN), and feedforward neural network (FFNN). <\/jats:p>","DOI":"10.1142\/s0219467822400071","type":"journal-article","created":{"date-parts":[[2021,12,23]],"date-time":"2021-12-23T15:12:04Z","timestamp":1640272324000},"source":"Crossref","is-referenced-by-count":7,"title":["A Review on Rice Crop Disease Classification Using Computational Approach"],"prefix":"10.1142","volume":"23","author":[{"given":"V.","family":"Malathi","sequence":"first","affiliation":[{"name":"School of Computer Science and Engineering, Vellore Institute of Technology, Vellore, Tamil Nadu, India"}]},{"given":"M. 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