Plant Leaf Disease Prediction Based On Deep Learning Using R2NN-WRS: Resnet Recurrent Neural Network and Watershed Region Segmentation Techniques
M.Udayadevi, G.Sivakumar
plant disease, deep learning, segmentation, agriculture, histogram, R2NN.
Plants are prone to various diseases during the growing season. It has a practical impact on global food security and the agricultural economy. Early diagnosis of plant diseases is one of the most challenging problems in agriculture. Not detecting the condition early can affect the overall yield and reduce farmers' profitability. However, agronomists and plant pathologists have traditionally used the naked eye test to detect leaf diseases. This traditional method of plant foliar disease detection is subjective, time-consuming, expensive, and requires a large number of personnel and a lot of information about plant disease. To tackle this problem, in this project we design Resnet Recurrent Neural Network (R2NN) algorithm is used to find plant disease. This first step is pre-processing using the Gaussian filter to enhance image quality. Then we apply Contrastive Limited Adaptive Equalization (CLAE) algorithm to improve image contrast. Furthermore, we use Watershed Region Segmentation (WRS) technique to segregate the affected parts. Later, the R2NN algorithm effectively classifies the plant disease. We show experimentally that our R2NN approach is more robust and extraordinary to generalize to unseen infected plant disease domain images than classical techniques. We also analyze the focus of attention as learned by our R2NN and show that our approach is capable of accurately locating infectious diseases in plants. Our approach has been tested on many plant species, so thus, the proposed method contributes to a more effective means of detecting and classifying plant disease.
Article Details
Unique Paper ID: 159185

Publication Volume & Issue: Volume 9, Issue 11

Page(s): 936 - 941
Article Preview & Download

Share This Article

Join our RMS

Conference Alert

NCSEM 2024

National Conference on Sustainable Engineering and Management - 2024

Last Date: 15th March 2024

Call For Paper

Volume 10 Issue 10

Last Date for paper submitting for March Issue is 25 June 2024

About Us enables door in research by providing high quality research articles in open access market.

Send us any query related to your research on

Social Media

Google Verified Reviews