A real-time approach of diagnosing rice leaf disease using deep learning-based faster R-CNN framework

A real-time approach of diagnosing rice leaf disease using deep learning-based faster R-CNN framework

The rice leaves related diseases often pose threats to the sustainable production of rice affecting many farmers around the world. Early diagnosis and appropriate remedy of the rice leaf infection is crucial in facilitating healthy growth of the rice plants to ensure adequate supply and food securit...

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Bibliographic Details
Main Authors: Bari, Bifta Sama, Islam, Md Nahidul, Rashid, Mamunur, Hasan, Md Jahid, Mohd Azraai, Mohd Razman, Musa, Rabiu Muazu, Ahmad Fakhri, Ab. Nasir, Majeed, Anwar P.P. Abdul
Format: Article
Language:English
Published: PeerJ Inc. 2021
Subjects:
QA75 Electronic computers. Computer science
QA76 Computer software
T Technology (General)
TJ Mechanical engineering and machinery
TK Electrical engineering. Electronics Nuclear engineering
Online Access:http://umpir.ump.edu.my/id/eprint/35164/
http://umpir.ump.edu.my/id/eprint/35164/1/A%20real-time%20approach%20of%20diagnosing%20rice%20leaf%20disease%20using%20deep%20learning-based%20faster%20R-CNN%20framework.pdf

Internet

http://umpir.ump.edu.my/id/eprint/35164/
http://umpir.ump.edu.my/id/eprint/35164/1/A%20real-time%20approach%20of%20diagnosing%20rice%20leaf%20disease%20using%20deep%20learning-based%20faster%20R-CNN%20framework.pdf

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