Deepak Kumar1, Vinay Kukreja1, Ayush Dogra1,*, Bhawna Goyal2, Talal Taha Ali3
CMC-Computers, Materials & Continua, Vol.77, No.2, pp. 2097-2121, 2023, DOI:10.32604/cmc.2023.044287
Abstract Wheat rust diseases are one of the major types of fungal diseases that cause substantial yield quality losses of
15%–20% every year. The wheat rust diseases are identified either through experienced evaluators or computerassisted techniques. The experienced evaluators take time to identify the disease which is highly laborious and too
costly. If wheat rust diseases are predicted at the development stages, then fungicides are sprayed earlier which
helps to increase wheat yield quality. To solve the experienced evaluator issues, a combined region extraction and
cross-entropy support vector machine (CE-SVM) model is proposed for wheat rust disease identification. In the
proposed… More >
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