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Review Paper on Leaf Diseases Detection and Classification Using Various CNN Techniques

Authors :
Manjeet Singh
Twinkle Dalal
Source :
Mobile Radio Communications and 5G Networks ISBN: 9789811571299
Publication Year :
2020
Publisher :
Springer Singapore, 2020.

Abstract

Majority of Indian population depends on agribusiness for its survival, and it plays a vital role in every nation’s economy. The disease is spread to other plants. Early detection of disease is a significant thing. Detection models to detect the disease are built by direct observation of every plant. This is essential as we can take parameters to restrict. Hence, healthy cropping is necessary for the growing agricultural economy. A better yield of crop is dependent on many factors including disease detection. The on time disease detection helps the farmers to save their crop yield as the remedies can be given on time. In order to solve the problem, various convolution neural network architectures have been designed and tested on labelled data to obtain high accuracy in classification and detection of disease. This work deals with the brief and detailed study of various techniques used for classification and detection of disease in plants based on feature extraction and different training methods.

Details

Database :
OpenAIRE
Journal :
Mobile Radio Communications and 5G Networks ISBN: 9789811571299
Accession number :
edsair.doi...........a2cae84080c4986d50de22d5e2f56a2f