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- W2885716239 abstract "Identication of plant disease is very important to prevent the loss and keep the harvest healthy. Determination of plant disease via visual monitoring is dicult and time consuming. In this paper, we described a method of detection and classication of plant disease using image processing and machine learning techniques. We used standard images of leaves of several types of plants to test our method. Initially, our method segments the input image to isolate disease parts of the leaf. Then we obtain various features from the diseased aected segmented image. Finally, we classify leaves into healthy and disease types based on its fea- tures using Multiclass Support Vector Machine (SVM) classier. Experimental results indicate that our method yields very high accuracy rate for detection and classication of plant diseases." @default.
- W2885716239 created "2018-08-22" @default.
- W2885716239 creator A5060958901 @default.
- W2885716239 date "2018-06-10" @default.
- W2885716239 modified "2023-09-23" @default.
- W2885716239 title "Detection and Classication of Plant Diseases Using Image Processing and Multiclass Support Vector Machine" @default.
- W2885716239 doi "https://doi.org/10.24294/jche.v0i0.547" @default.
- W2885716239 hasPublicationYear "2018" @default.
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