• Pinki
• Dr. Rohit Kumar Singhal

Improvement of adjusted disease acknowledgment and portrayal structure is essentially investigated in cultivation. In the recent many years, specialists have reviewed several social orders abusing various pieces of a plant. A for all intents and purposes indistinguishable report is performed for Soybean utilizing leaf pictures. A standard based self-loader framework utilizing musings of k-suggests is coordinated and executed to see solid leaves from diseased leaves. The use relies upon the requesting of the disease on the leaf or recognize the sound leaf, and the Alternaria Alternata , Anthracnose ,Bacterial Blight, Cercospora Leaf Spot or Healthy Leaf. Assessments are performed by uninhibitedly using covering highlights, surface elements, and their blends to prepare three models subject to help Multi-class Support vector machine classifier. Results are made utilizing endless pictures gathered from Plant Village dataset.

Plant Disease Detection , Multiclass SVM , Support Vector Machine , K-Means

" Identification of Plant Diseases using K-Means Segmentation and Multi-Class based SVM", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.8, Issue 10, page no.d706-d711, October-2021, Available :http://www.jetir.org/papers/JETIR2110376.pdf

" Identification of Plant Diseases using K-Means Segmentation and Multi-Class based SVM", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.8, Issue 10, page no. ppd706-d711, October-2021, Available at : http://www.jetir.org/papers/JETIR2110376.pdf