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INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT International Peer Reviewed & Refereed Journals, Open Access Journal ISSN Approved Journal No: 2456-4184 | Impact factor: 8.76 | ESTD Year: 2016 Scholarly open access journals, Peer-reviewed, and Refereed Journals, Impact factor 8.76 (Calculate by google scholar and Semantic Scholar | AI-Powered Research Tool) , Multidisciplinary, Monthly, Indexing in all major database & Metadata, Citation Generator, Digital Object Identifier(DOI) |
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| Paper Title: | TO PROPOSE CLASSIFICATION TECHNIQUE FOR PLANT DISEASE DETECTION USING IMAGE PROCESSING |
| Authors Name: | Tunav Garg , Penugonda Hemanth Kumar , Prof(Dr) Shailendra Narayan Singh |
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IJNRD_195185
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| Published Paper Id: | IJNRD2305330 |
| Published In: | Volume 8 Issue 5, May-2023 |
| DOI: | |
| Abstract: | The use of image processing techniques for plant disease detection has become increasingly popular due to the growing demand for efficient and reliable plant disease diagnosis. This research paper proposes a classification technique for plant disease detection using image processing. The proposed technique employs a deep learning approach based on convolutional neural networks (CNNs) for feature extraction and classification. The proposed technique is designed to detect and classify plant diseases by analyzing images of leaves, stems, and fruits. The dataset used for training and testing the model consists of high-quality images of healthy and diseased plants. The proposed technique achieves high accuracy in classifying the images into different categories of plant diseases. The research paper presents an experimental evaluation of the proposed technique using different performance metrics such as accuracy, precision, recall, and F1 score. The results demonstrate that the proposed technique is highly effective in accurately identifying plant diseases and can be used as a reliable tool for plant disease detection in agriculture. This research paper contributes to the development of image processing techniques for plant disease detection and provides a practical solution for improving crop yields and preventing crop losses caused by plant diseases. |
| Keywords: | — image processing, CNN’s, pre-processing, Segmentation, feature extraction, texture analysis, VGG-16 |
| Cite Article: | "TO PROPOSE CLASSIFICATION TECHNIQUE FOR PLANT DISEASE DETECTION USING IMAGE PROCESSING", International Journal of Novel Research and Development (www.ijnrd.org), ISSN:2456-4184, Vol.8, Issue 5, page no.d220-d223, May-2023, Available :http://www.ijnrd.org/papers/IJNRD2305330.pdf |
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| ISSN: |
2456-4184 | IMPACT FACTOR: 8.76 Calculated By Google Scholar| ESTD YEAR: 2016 An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.76 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:IJNRD2305330 Registration ID: 195185 Published In: Volume 8 Issue 5, May-2023 DOI (Digital Object Identifier): Page No: d220-d223 Country: Faridabad, Haryana, India Research Area: Computer Science & Technology Publisher : IJ Publication Published Paper URL : https://www.ijnrd.org/viewpaperforall?paper=IJNRD2305330 Published Paper PDF: https://www.ijnrd.org/papers/IJNRD2305330 |
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ISSN: 2456-4184
Impact Factor: 8.76 and ISSN APPROVED
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