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- W4289209310 abstract "Maintaining croplands are one of the critical problems for the Indian economy. Therefore, malady identification in plants plays a critical role in the agriculture sector, as ailment in crops is a natural occurrence. Agricultural production with high quality is a must for any country's economic development. Therefore, recognizing the perishing fields can be considered as a solution for avoiding crop loss and productivity decrease. The conventional approach to disease identification and classification necessitates a significant amount of time, a great deal of effort, and ongoing farm surveillance. In recent years, technological advancements and researcher's emphasizing on this field have made it possible to obtain an optimized solution. Various common methods from the fields of machine learning, image analysis, and classification approaches have been used to recognize and detect diseases in agricultural products. This study outlines different existing strategies for detecting agricultural product diseases. Besides, the paper examines the methodologies that have been used to diagnose diseases, segment the affected areas, and classify diseases. It also provides a description of different techniques for (i) feature extraction, (ii) segmentation, and (iii) classifiers and their advantages and disadvantages." @default.
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- W4289209310 date "2022-01-01" @default.
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- W4289209310 title "Survey on Machine Learning Algorithm for Leaf Disease Detection Using Image Processing Techniques" @default.
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- W4289209310 doi "https://doi.org/10.1007/978-981-19-1012-8_47" @default.
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