This paper is published in Volume-7, Issue-2, 2021
Area
Electronics and Communication Engineering
Author
Nisha Sharma, Dr. Sukhvinder Kaur, Dr. Rahul Malhotra
Org/Univ
Swami Devi Dayal Institute of Engineering and Technology, Panchkula, Haryana, India
Pub. Date
30 March, 2021
Paper ID
V7I2-1265
Publisher
Keywords
Image Processing, Image Segmentation, K-Mean Clustering, Feature Extraction, CNN

Citationsacebook

IEEE
Nisha Sharma, Dr. Sukhvinder Kaur, Dr. Rahul Malhotra. Improved plant leaf disease classification by optimizing weight with convolution neural network learning approach, International Journal of Advance Research, Ideas and Innovations in Technology, www.IJARIIT.com.

APA
Nisha Sharma, Dr. Sukhvinder Kaur, Dr. Rahul Malhotra (2021). Improved plant leaf disease classification by optimizing weight with convolution neural network learning approach. International Journal of Advance Research, Ideas and Innovations in Technology, 7(2) www.IJARIIT.com.

MLA
Nisha Sharma, Dr. Sukhvinder Kaur, Dr. Rahul Malhotra. "Improved plant leaf disease classification by optimizing weight with convolution neural network learning approach." International Journal of Advance Research, Ideas and Innovations in Technology 7.2 (2021). www.IJARIIT.com.

Abstract

Agricultural productivity is something on which the economy highly depends. This is one of the reasons that disease detection in plants plays a vital role in the agriculture field, as having the disease in plants is quite natural. If proper care is not taken in this area, then it causes severe effects on plants and due to which respective product quality, quantity, or productivity is affected. In synopsis proposed approach optimized segmentation to find an active area for features and reduce noise, then extract texture base features and learning by ensemble classifier approach. In the Proposed framework main emphasis on getting sufficient features from disease and learning a combination of Convolution and nonlinear classification function.
Paper PDF