Abstract
PaperThe paper presents the implementation of various machines learning approach for the diagnosis of leaf diseases. For analysis data collection were done towards capturing the images of pumpkin leaf affected by different diseases. The pumpkin leaf samples were taken. The samples correspond to the blight and fungal problems like Alternaria, Powdery Mildew Anthracnose, and Yellow Vine Disease etc. The methods for analysis were implemented and tested which are based on time, frequency and statistical approach. For classification machine learning approaches like neural networks, SVM, KNN etc were analyzed. The implementation issues were presented for future work.
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