Plant Disease Identification Using Deep Learning and Transfer Learning

There is a dire need to understand plant diseases and its effect on agricultural productivity. Agriculture takes up substantial amount of India’s economy. The spread of plant disease in India poses a heavy challenge to crop yield, thereby directly impacting livelihood of millions of farmers across India. Through this work, we will be presenting two approaches based on CNN (Convolutional Neural Networks) and VGG19 to improve accuracy of existing solutions. PlantVillage dataset is used for training as well as testing the models, which contains 21,000+ images. The first model based on CNN has a accuracy of 93.82% and the second model based on VGG19 has a accuracy of 88.93%. Our work is mainly focused on comparing the results of our models with some previous manuscripts based on the same dataset and how we achieved greater accuracy.

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Publication Details

Journal
Procedia Computer Science
Published
2025-01-01
DOI
https://doi.org/10.1016/j.procs.2025.03.210
Primary Topic
Smart Agriculture and AI
Type
article
Field-Weighted Citation Impact
0.00
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article

Plant Disease Identification Using Deep Learning and Transfer Learning

Ravindra Yadav, Anita Seth, Ansh Sharma, Meet Ganpatlal Oza
Procedia Computer Science
Smart Agriculture and AI
article

Plant Disease Identification Using Deep Learning and Transfer Learning

Ravindra Yadav, Anita Seth, Ansh Sharma, Meet Ganpatlal Oza
article en

Abstract

There is a dire need to understand plant diseases and its effect on agricultural productivity. Agriculture takes up substantial amount of India’s economy. The spread of plant disease in India poses a heavy challenge to crop yield, thereby directly impacting livelihood of millions of farmers across India. Through this work, we will be presenting two approaches based on CNN (Convolutional Neural Networks) and VGG19 to improve accuracy of existing solutions. PlantVillage dataset is used for training as well as testing the models, which contains 21,000+ images. The first model based on CNN has a accuracy of 93.82% and the second model based on VGG19 has a accuracy of 88.93%. Our work is mainly focused on comparing the results of our models with some previous manuscripts based on the same dataset and how we achieved greater accuracy.

Procedia Computer ScienceVol. 260
Devi Ahilya Vishwavidyalaya (IN)
Openalex Percentile: Top 92%
Smart Agriculture and AI
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