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An Experiment to Find Disease Detection for Rice Plants Using ResNet
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Author(s): Sekar R. (Koneru Lakshimaiah Education Foundation, India), Hema Likhitha Godavarthi (Koneru Lakshmaiah Education Foundation, India), Satya Deepika Bandi (Koneru Lakshmaiah Education Foundation, India), Sri Vandhana Dadi (Koneru Lakshmaiah Education Foundation, India) and K. Praghash (Koneru Lakshmaiah Education Foundation, India)
Copyright: 2022
Pages: 21
Source title:
Advanced Practical Approaches to Web Mining Techniques and Application
Source Author(s)/Editor(s): Ahmed J. Obaid (University of Kufa, Iraq), Zdzislaw Polkowski (Wroclaw University of Economics, Poland) and Bharat Bhushan (Sharda University, India)
DOI: 10.4018/978-1-7998-9426-1.ch013
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Abstract
In India, around 70% of the populace depends on agribusiness. The identification of plant infections is significant to forestall misfortunes inside the yield. It's problematic to notice plant illnesses physically. It needs a colossal amount of work, skill inside the plant infections, and conjointly needs an unreasonable time stretch. Subsequently, picture handling models can be utilized for the location of plant illnesses. In this venture, the authors have depicted the procedure for the discovery of imperfections of plant illnesses with the assistance of their leaves pictures. Here they are utilizing the rice plant for recognizing the deformities. Picture handling is a part of sign handling, which can separate the picture properties or valuable data from the picture. The shade of leaves, measure of harm to leaves, space of the leaf, surface boundaries are utilized for arrangement. In this task, the authors have examined diverse picture boundaries or highlights to recognize distinctive plant passes on infections to accomplish the best accuracy.
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