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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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Issue: December 2025
Volume 10 | Issue 12
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Impact Factor : 8.14
Issue per Year : 12
Volume Published : 10
Issue Published : 115
Article Submitted : 19463
Article Published : 8041
Total Authors : 21252
Total Reviewer : 769
Total Countries : 145
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| Paper Title: | Plant Disease Detection Using CNN Model |
| Authors Name: | Anshuman Kalbhor , Aditya Lagas , Sania Gupta , Saurabh Koli , Manisha Desai |
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| Author Reg. ID: |
IJRTI_202539
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| Published Paper Id: | IJRTI2504235 |
| Published In: | Volume 10 Issue 4, April-2025 |
| DOI: | |
| Abstract: | A major problem in the agriculture industry is the identification and management of plant diseases. Identification of plant diseases is the key to prevent losses in the yield and quantity of agricultural products. Preventing losses in agricultural product production and quantity requires the identification of plant diseases. Detecting plant diseases quickly and accurately is essential to raising agricultural output in a sustainable manner. This article analyses the application of deep learning techniques for plant disease identification through a CNN model incorporated in a mobile application developed in Flutter. The system provides farmers with instant classification and suggested treatments for images taken of infected part of plants. The model is trained using a dataset of plant leaf images captured in both infected and healthy conditions and converted to TensorFlow Lite (TFLite) format for rapid inference on mobile devices. Experimental results show that the model achieves a training accuracy of 96.56% and testing accuracy of 96.20%, demonstrating its reliability in real-world applications. This research illustrates the contribution of AI-enabled mobile apps in agricultural development. |
| Keywords: | CNN, Deep learning, mobile application, plant disease detection, TensorFlow Lite. |
| Cite Article: | "Plant Disease Detection Using CNN Model", International Journal of Science & Engineering Development Research (www.ijrti.org), ISSN:2455-2631, Vol.10, Issue 4, page no.c98-c101, April-2025, Available :http://www.ijrti.org/papers/IJRTI2504235.pdf |
| Downloads: | 000412 |
| 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: IJRTI2504235
Registration ID:202539
Published In: Volume 10 Issue 4, April-2025
DOI (Digital Object Identifier):
Page No: c98-c101 Country: Pune, Maharashtra, India Research Area: Computer Engineering Publisher : IJ Publication Published Paper URL : https://www.ijrti.org/viewpaperforall?paper=IJRTI2504235 Published Paper PDF: https://www.ijrti.org/papers/IJRTI2504235 |
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ISSN: 2456-3315
Impact Factor: 8.14 and ISSN APPROVED,
Journal Starting Year (ESTD) : 2016
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