Detection of Diseases in Flora Through Leaf Image Classification by Convolution Neural Network
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Abstract
The quality of human existence and economic standing are significantly impacted by agriculture. It is the foundation of a nation's economic structure. Therefore, early diagnosis of plant diseases is crucial in both the agricultural sector and in people's daily life. Hunger and starvation are caused by agricultural losses due to plant diseases, especially in less developed nations where access to disease-controlling measures is limited and yearly losses of 30 to 50 percent for main crops are not unusual. Due to inadequate diagnosis of plant diseases, many plants die. Initially, diagnosis of plant disease was performed using MATLAB and machine learning algorithms including SVM. But these diagnoses did not provide accurate results. Also, in previous works website has not been created. To overcome this problem, a CNN model has been proposed that detects plant diseases. This CNN model has been deployed to the website. On this website, the image can be uploaded, and the disease gets predicted according to the image. The detected disease gets displayed on the website. To the CNN model, 15 cases have been fed, including both healthy and unhealthy leaves. The proposed model achieves a greater accuracy of more than 95%. This work offers a major benefit to the farmers by helping them in detecting plant diseases without requiring any special hardware or software.
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References
Plant Disease Detection Using CNN by Garima Shrestha, Deepsikha, Majolica Das, Naiwrita Dey published in Proceedings of 2020 IEEE Applied Signal Processing Conference (ASPCON), 2020
Bashish, D.A., Braik, M., Ahmad, S.B., ‘A Framework for Detection and Classification of Plant Leaf and Stem Diseases’, International Conference on Signal and Image Processing, pp. 113-118, 2010
Kulkarni Anand H, Ashwin Patil RK. Applying image processing technique to detect plant diseases. Int J Mod Eng Res 2012;2(5):3661–4
Kutty, Suhaili Beeran, Noor Ezan Abdullah, Habibah Hashim, and Aida Sulinda. “Classification of Watermelon Leaf Diseases Using Neural Network Analysis.” In Business Engineering and Industrial Applications Colloquium (BELAC), 2013 IEEE, pp. 459-464. IEEE, 2013.
Bhange, M., Hingoliwala, H.A., ‘Smart Farming: Pomegranate Disease Detection Using Image Processing’, Second International Symposium on Computer Vision and the Internet, Volume 58, pp. 280-288, 2015
Malvika Ranjan, Manasi Rajiv Weginwar, NehaJoshi, Prof.A.B. Ingole, “detection and classification of leaf disease using artificial neural network”, International Journal of Technical Research and Applications, 2015
Pranjali B. Padol, Prof. AnjilA.Yadav, "SVM Classifier Based Grape Leaf Disease Detection" 2016 Conference on Advances in Signal Processing(CAPS) Cummins college of Engineering for Women, Pune. June 9-11, 2016.
Varsha P. Gaikwad, Vijaya Musande, 2017 Wheat disease detection using image processing First International Conference on Intelligent Systems and Information Management (ICISIM) (2017)
Plant Leaf Disease Detection and Classification Based on CNN with LVQ Algorithm by Melike Sardogan, Adem Tuncer, Yunus Ozen in 3rd International Conference on Computer Science and Engineering, 2018
Gharte Sneha H., Prof. (Dr.) S. B. Bagal, “Plant Leaf Disease Detection Using Image Processing”, International Research Journal of Engineering and Technology (IRJET), Volume: 06 Issue: 06 | June 2019.