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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 14 | Issue 8 | Month- August 2026
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Paper Title
AUTOMATED PHYTOPATHOLOGICAL DIAGNOSIS AND CLASSIFICATION EMPLOYING DEEP CONVOLUTIONAL NETWORKS
Authors
SHAIK RAHAMAN, Y V NAGESH MEESALA, S SRINADH RAJU
Keywords
deep learning, CNN, MobileNetV2, image classification, smart agriculture.
Abstract
Plant species classification and leaf disease detection are essential in modern agriculture for improving crop productivity and reducing losses. Traditional manual inspection methods are time-consuming and inefficient for bulky applications. This work presents a deep learning-based approach for automated plant species and disease classification using MobileNetV2 and ResNet50 models. MobileNetV2 is used for efficient plant species recognition, while ResNet50 is applied for accurate disease detection from leaf images. Experimental results demonstrate that the proposed system achieves high classification accuracy and better efficiency compared to conventional methods. The developed framework supports real-time crop monitoring and disease diagnosis, contributing to smart and sustainable agricultural applications.
IJCRT's Publication Details
Unique Identification Number - IJCRT2606053
Paper ID - 309774
Page Number(s) - a428-a434
Pubished in - Volume 14 | Issue 6 | June 2026
DOI (Digital Object Identifier) -
Publisher Name - IJCRT | www.ijcrt.org | ISSN : 2320-2882
E-ISSN Number - 2320-2882
Cite this article
SHAIK RAHAMAN, Y V NAGESH MEESALA, S SRINADH RAJU, "AUTOMATED PHYTOPATHOLOGICAL DIAGNOSIS AND CLASSIFICATION EMPLOYING DEEP CONVOLUTIONAL NETWORKS", International Journal of Creative Research Thoughts (IJCRT), ISSN:2320-2882, Volume.14, Issue 6, pp.a428-a434, June 2026, Available at :http://www.ijcrt.org/papers/IJCRT2606053.pdf
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Volume 14 | Issue 8
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August 2026
Volume 14 | Issue 8
Last Date :
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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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