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International Journal for Research Trends and Innovation
International Peer Reviewed & Refereed Journals, Open Access Journal
ISSN Approved Journal No: 2456-3315 | Impact factor: 8.14 | ESTD Year: 2016
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Impact Factor : 8.14
Issue per Year : 12
Volume Published : 10
Issue Published : 113
Article Submitted : 18006
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| Paper Title: | Comparative Analysis of Rice and Wheat Plant Leaf Disease Classification |
| Authors Name: | P. Sindhu , Dr. G. Indirani |
| Download E-Certificate: | Download |
| Author Reg. ID: |
IJRTI_184234
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| Published Paper Id: | IJRTI2211070 |
| Published In: | Volume 7 Issue 11, November-2022 |
| DOI: | |
| Abstract: | The field of plant disease detection using image classification has recently exploded in popularity. Using image processing algorithms, plant illnesses can be identified to help farmers to save their agricultural products and avoid financial losses. Smart Grids, Surveillance, Smart houses, and so on are just a few examples of how IoT is being used today. Using IoT and networking technologies, Precision Agriculture aims to boost the yield of the farm's crops. There is a lot of interest in using machine learning (ML) techniques to identify illnesses in plant photos. Several steps are included in the procedure, including picture acquisition, preprocessing, segmentation and feature extraction. To begin, images will be captured via IoT devices and stored on a cloud server, where they will be processed for classification. The rice plant photos are being preprocessed in the cloud to improve the image quality. A Comparative analysis of rice plant and wheat plant disease identification and classification is presented. The disease detection of a wheat leaf is then segmented using the fuzzy c-means (FCM) and multi-class classification is performed using probabilistic neural networks (PNN). For rice plant disease classification, Deep Neural Network (DNN) and Grey Wolf Optimization Algorithm (GWO) are used to evaluate the comparative performance. The effectiveness of the proposed method's classification performance was compared by a thorough experimentation. |
| Keywords: | Wheat Plat Leaf, rice plant leaf, Fuzzy C-Means, Machine Learning, Probabilistic neural network. |
| Cite Article: | "Comparative Analysis of Rice and Wheat Plant Leaf Disease Classification", International Journal of Science & Engineering Development Research (www.ijrti.org), ISSN:2455-2631, Vol.7, Issue 11, page no.487 - 494, November-2022, Available :http://www.ijrti.org/papers/IJRTI2211070.pdf |
| Downloads: | 000205139 |
| ISSN: |
2456-3315 | IMPACT FACTOR: 8.14 Calculated By Google Scholar| ESTD YEAR: 2016 An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.14 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator |
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Published Paper ID: IJRTI2211070
Registration ID:184234
Published In: Volume 7 Issue 11, November-2022
DOI (Digital Object Identifier):
Page No: 487 - 494 Country: -, -, - Research Area: Engineering Publisher : IJ Publication Published Paper URL : https://www.ijrti.org/viewpaperforall?paper=IJRTI2211070 Published Paper PDF: https://www.ijrti.org/papers/IJRTI2211070 |
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ISSN: 2456-3315
Impact Factor: 8.14 and ISSN APPROVED,
Journal Starting Year (ESTD) : 2016
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