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INTERNATIONAL JOURNAL OF CREATIVE RESEARCH THOUGHTS - IJCRT (IJCRT.ORG)
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ISSN Approved Journal No: 2320-2882 | Impact factor: 7.97 | ESTD Year: 2013
Call For Paper - Volume 13 | Issue 12 | Month- December 2025
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Paper Title
POTATO DISEASE IDENTIFICTION USING DEEP LEARNING
Authors
Harshith K L, Deepa V B, Adarsh N Hiremath, Gurukiran B Banakar, Jayanth A Gatti
Keywords
Potato disease identification, deep learning, CNNs, late blight, early blight, image classification, agricultural technology.
Abstract
Potato diseases, such as late blight and early blight, pose significant threats to global agricultural productivity. Manual disease detection is time-intensive and error-prone, necessitating automated solutions. This study proposes a deep learning-based system using Convolutional Neural Networks (CNNs) for identifying potato leaf diseases. The model was trained and tested on an augmented dataset, achieving a classification accuracy of 97%. It effectively distinguishes healthy leaves from diseased ones. The system's robustness is validated through cross-validation and practical testing. Key advantages include high accuracy and scalability for agricultural applications. The approach can be extended for real-time use through IoT devices. This work aims to assist farmers in early disease detection, reducing crop losses and enhancing productivity.
IJCRT's Publication Details
Unique Identification Number - IJCRT2501037
Paper ID - 275144
Page Number(s) - a349-a351
Pubished in - Volume 13 | Issue 1 | January 2025
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Publisher Name - IJCRT | www.ijcrt.org | ISSN : 2320-2882
E-ISSN Number - 2320-2882
Cite this article
Harshith K L, Deepa V B, Adarsh N Hiremath, Gurukiran B Banakar, Jayanth A Gatti, "POTATO DISEASE IDENTIFICTION USING DEEP LEARNING", International Journal of Creative Research Thoughts (IJCRT), ISSN:2320-2882, Volume.13, Issue 1, pp.a349-a351, January 2025, Available at :http://www.ijcrt.org/papers/IJCRT2501037.pdf
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Volume 13 | Issue 12
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Submit Manuscript Online Impact Factor: 7.97 Review Results : Within 02-03 Days Paper Publication : Within 02-03 Days
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ISSN: 2320-2882 Impact Factor: 7.97 and ISSN APPROVED Journal Starting Year (ESTD) : 2013
ISSN and 7.97 Impact Factor Details
ISSN: 2320-2882 Impact Factor: 7.97 and ISSN APPROVED Journal Starting Year (ESTD) : 2013
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