Detecting and Classifying Plant Diseases Automatically Using Machine Learning Algorithms
Keywords:
K - Nearest Neighbor, Support Vector Machine and Convolutional Neural Network.Abstract
Food production must rise in tandem with the rapid growth of the human population. Diseases that spread quickly can seriously reduce plant yields and possibly wipe off entire crops. It is essential to increase food production given the rapidly expanding world population. But the danger of quickly spreading illnesses is real, with the potential to completely destroy agricultural products as well as severely damage crop yields. Acknowledging the critical significance of early disease identification and prevention, this study explores innovative approaches that leverage the widespread availability of cell phones, even in the most remote rural locations. This research focuses on the application of automated image analysis as a workable substitute for traditional methods that depend on expensive laboratory processes and human expertise—materials that are frequently noticeably lacking in less developed areas. The study carefully compares the efficacy of latest developments in deep learningtechniques with more conventional machine learning algorithms to present the most recent developments in this rapidly developing subject. The main objective is to improve agricultural practices to lessen the detrimental effects of disease on crop yields and promote sustainable food production in light of the world's rapidly growing population.
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