• Nitesh Gupta
• Neeraj Jain

Improvement of adjusted disease acknowledgment and portrayal structure is essentially investigated in agriculture. In the recent decades, specialists have assessed a few social requests abusing various bits of a plant. An essentially indistinguishable report is performed for Soybean utilizing leaf pictures. A standard based self-loader framework utilizing contemplations of k-suggests is composed and executed to see solid leaves from diseased leaves. The use relies upon the requesting of the disease on the leaf or recognize the solid leaf, and the Alternaria Alternata , Anthracnose ,Bacterial Blight, Cercospora Leaf Spot or Healthy Leaf. Assessments are performed by unreservedly using disguising highlights, surface highlights, and their blends to prepare three models subject to help Multi-class Support vector machine classifier. Results are made utilizing incalculable pictures collected from Plant Village dataset. Worthy customary exactness respects are spoken to all the considered blends which are likewise observed to be superior to existing ones.

"Plant Leaf Disease Detection and Classification using Modified SVM Classifier ", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.6, Issue 6, page no.108-115, June 2019, Available :http://www.jetir.org/papers/JETIR1907A40.pdf

"Plant Leaf Disease Detection and Classification using Modified SVM Classifier ", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.6, Issue 6, page no. pp108-115, June 2019, Available at : http://www.jetir.org/papers/JETIR1907A40.pdf