Year: 2026
Type: article
Abstract: Agriculture plays a vital role in global food security, yet plant diseases continue to cause significant losses in crop yield and quality. This paper presents LeafScan AI, an intelligent plant disease detection system based on a Dual Self-Attention Residual Network (DSRN). The proposed model integrates deep residual learning with spatial and channel attention mechanisms to enhance feature extraction from plant leaf images. Experimental results demonstrate 93.40% accuracy, 91.20% sensitivity, 94.10% specificity, and 92.85% AUC, outperforming existing CNN-based baselines.
Authors: Harshitha S, Ishwarya S, Janani I
Language: English
Topic: Smart Agriculture and AI
Subfield: Plant Science
Domain: Life Sciences
SDG: Zero hunger
Open Access status: bronze
OpenAlex ID: W7160944643
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