K-means- SVM To Predict Diseases From Fruits In Agriculture Data

M. Akhila, A. L. Prasanna, T. N. S. P. Nikita, T. Prasanna, P. P. Sowmya, R. John Mathew


A fruit disease's early discovery is crucial since it will harm the agricultural sector. This work focuses mostly on the identification and analysis of fruit illnesses that are present in plant regions, as well as the documentation of the agricultural sector. In this study, the author uses the SVM algorithm and KMEANS segmentation to forecast fruit illnesses. When using KMEANS segmentation, similar colour clusters can be created. Clustering features are then utilised to train the SVM classifier, which uses those features to determine if an input image is normal or has a disease.


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