Optimized classification of potato leaf disease using EfficientNet-LITE and KE-SVM in diverse environments

The model's efficiency and improved accuracy render it especially appropriate for settings with constrained computational resources, such as mobile or edge devices, offering substantial practical advantages for precision agriculture.

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Publication Details

Journal
Frontiers in Plant Science
Published
2025-05-02
DOI
https://doi.org/10.3389/fpls.2025.1499909
Citations
14
Primary Topic
Smart Agriculture and AI
Type
article
Field-Weighted Citation Impact
24.50
Controls
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article

Optimized classification of potato leaf disease using EfficientNet-LITE and KE-SVM in diverse environments

V. Rajasekar, G Sangar
14 citations
Frontiers in Plant Science
Smart Agriculture and AI
24.50
article

Optimized classification of potato leaf disease using EfficientNet-LITE and KE-SVM in diverse environments

V. Rajasekar, G Sangar
article en
14 citations

Abstract

The model's efficiency and improved accuracy render it especially appropriate for settings with constrained computational resources, such as mobile or edge devices, offering substantial practical advantages for precision agriculture.

Frontiers in Plant ScienceVol. 16
SRM Institute of Science and Technology (IN)
Zero hunger
Openalex Percentile: Top 0%
Smart Agriculture and AI
24.50
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Optimized classification of potato leaf disease using EfficientNet-LITE and KE-SVM in diverse environments — V. Rajasekar, G Sangar · Frontiers in Plant Science (2025) | TGRS Research Map | TGRS