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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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Issue: May 2024
Volume 9 | Issue 5
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Impact Factor : 8.76
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| Paper Title: | APPLICATION ON DETECTING AND TREATING THE DISEASE IN PLANT/CROPS |
| Authors Name: | J.Lethisia Nithiya , G Ajay Simha Reddy , G Sai nithin , G.N Yuva Simha Reddy |
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| Author Reg. ID: |
IJNRD_217102
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| Published Paper Id: | IJNRD2404161 |
| Published In: | Volume 9 Issue 4, April-2024 |
| DOI: | |
| Abstract: | Rapid improvements in deep learning (DL) techniques have made it possible to detect and recognize objects from images. DL approaches have recently entered various agricultural and farming applications after being successfully employed in various fields. Automatic identification of plant diseases can help farmers manage their crops more effectively, resulting in higher yields. Detecting plant disease in crops using images is an intrinsically difficult task. In addition to their detection, individual species identification is necessary for applying tailored control methods. A survey of research initiatives that use convolutional neural networks (CNN), a type of DL, to address various plant disease detection concerns was undertaken in the current publication. In this work, we have reviewed 100 of the most relevant CNN articles on detecting various plant leaf diseases over the last five years. In addition, we identified and summarized several problems and solutions corresponding to the CNN used in plant leaf disease detection. Moreover, Deep convolutional neural networks (DCNN) trained on image data were the most effective method for detecting early disease detection. We expressed the benefits and drawbacks of utilizing CNN in agriculture, and we discussed the direction of future developments in plant disease detection. |
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| Cite Article: | "APPLICATION ON DETECTING AND TREATING THE DISEASE IN PLANT/CROPS", International Journal of Novel Research and Development (www.ijnrd.org), ISSN:2456-4184, Vol.9, Issue 4, page no.b467-b473, April-2024, Available :http://www.ijnrd.org/papers/IJNRD2404161.pdf |
| Downloads: | 00046 |
| 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:IJNRD2404161 Registration ID: 217102 Published In: Volume 9 Issue 4, April-2024 DOI (Digital Object Identifier): Page No: b467-b473 Country: kanchipuram, tamil nadu, India Research Area: Engineering Publisher : IJ Publication Published Paper URL : https://www.ijnrd.org/viewpaperforall?paper=IJNRD2404161 Published Paper PDF: https://www.ijnrd.org/papers/IJNRD2404161 |
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ISSN: 2456-4184
Impact Factor: 8.76 and ISSN APPROVED
Journal Starting Year (ESTD) : 2016
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