National Academy of Agricultural Sciences (NAAS)
|
PRINT ISSN : 2319-7692
Online ISSN : 2319-7706 Issues : 12 per year Publisher : Excellent Publishers Email : editorijcmas@gmail.com / submit@ijcmas.com Editor-in-chief: Dr.M.Prakash Index Copernicus ICV 2018: 95.39 NAAS RATING 2020: 5.38 |
Deep learning is the modern technique used for image processing. Particularly Convolutional Neural Networks (CNNs), is used for automatic identification of cotton Plant disease. Disease in cotton can interfere with the production of cotton and makes a distress to the country’s economy. To manage the disease in cotton, an accurate diagnosis is essential. In this paper, to diagnosis the disease in cotton a research was carried out to automatically identify the cotton plant disease using Convolutional Neural Networks. Dataset with around 13,372 images for three diseases such as Bacterial Blight, Anthracnose, and Leafhopper are collected from cotton field. Convolutional Neural Networks is used to for both recognition and classification of three cotton disease images captured from farmer’s field. The experimental result showed affirmative output of approximately 93.89 % accuracy of recognition of cotton plant disease using python programming.
Citations |
 |
 |
 |
 |
