Potato Plant Leaf Disease Detection using optimized CNN and Transfer Learning

The plant disease is a significant concern in the agriculture field. Many diseases destroy the crop badly. Optimized Convolutional neural network (CNN) model having seven convolutional layer with weight pruning is used for detecting disease on potato leaves. Further transfer learning is used to compare the results of the proposed model. Plant Village dataset which contains potato disease-Early blight and late blight is used. Both the diseases are fungaldiseases. Used transfer learning models are Resnet50, VGG16 and VGG19.

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Publication Details

Published
2024-11-21
DOI
https://doi.org/10.1109/ic-sit63503.2024.10862536
Primary Topic
Smart Agriculture and AI
Type
article
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article

Potato Plant Leaf Disease Detection using optimized CNN and Transfer Learning

Shweta Agrawal, R. G. Karandikar
Smart Agriculture and AI
article

Potato Plant Leaf Disease Detection using optimized CNN and Transfer Learning

Shweta Agrawal, R. G. Karandikar
article en

Abstract

The plant disease is a significant concern in the agriculture field. Many diseases destroy the crop badly. Optimized Convolutional neural network (CNN) model having seven convolutional layer with weight pruning is used for detecting disease on potato leaves. Further transfer learning is used to compare the results of the proposed model. Plant Village dataset which contains potato disease-Early blight and late blight is used. Both the diseases are fungaldiseases. Used transfer learning models are Resnet50, VGG16 and VGG19.

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Potato Plant Leaf Disease Detection using optimized CNN and Transfer Learning — Shweta Agrawal, R. G. Karandikar · (2024) | TGRS Research Map | TGRS