Automated Quality Assessment of Crops Using CNN - Keras
DOI:
https://doi.org//10.32628/CSEIT2173186Keywords:
Image Preprocessing, Classification, Convolutional Neural Network, Keras, Deep Learning.Abstract
Plant disease is an on-going challenge for the farmers and it has been one of the major threats to the income and the food security. This project is used to classify plant leaf into diseased and healthy leaf,to improve the quality and quantity of agricultural production in the country. The innovative technology that helps in improve the quality and quantity in the agricultural field is the smart farming system. It represented the modern method that provides cost-effective disease detection and deep learning with convolutional neural networks (CNNs) has achieved large successfulness in the categorisation of different plant leaf diseases. CNN reads a really very larger picture in a simple way. CNN nearly utilised to examine visual imagery and are frequently working behind the scenes in image classification. To extract the general features and then classify them under multiple based upon the features detected. This project will help the farmers financially in increasing the production of the crop yield as well as the overall agricultural production. The paper reviews the expected methods of plant leaf disease detection system that facilitates the advancement in agriculture. It includes various phases such as image preprocessing, image classification, feature extraction and detecting healthy or diseased.
References
- Bhange, M., Hingoliwala, H.A., 'Smart Farming: Pomegranate Disease Detection Using Image Processing', Second International Symposium on Computer Vision and the Internet, Volume58, 2015 .
- Chit Su Hlaing, SaiMaungMaungZaw, "Plant Diseases Recognition for Smart Farming based Statistical Features".
- Saradhambal, G., Dhivya, R., Latha, S., Rajesh, R, 'Plant Disease Detection and its Solution using Image Classification', International Journal of Pure and Applied Mathematics, Volume 119, Issue 14, 2018
- Singh, V., Misra, A.K., 'Detection of Plant Leaf Diseases Using Image Segmentation and Soft Computing Techniques', Information Processing in Agriculture, Volume 8, 2016 .
- Pujari, J.D, Yakkundimath, R., Byadgi, A.S, ‘Image Processing Based Detection of Fungal Diseases In Plants’, International Conference on Information and Communication Technologies, Volume 46, 2015
- XiaoyanGuo, MingZhang, Yongqiang Dai,image of plant disease segmentation model based on pulse coupled neural Network with shuffle frog leap algorithm"
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