Multi-Stage Vision Transformer and Knowledge Graph Fusion for Enhanced Plant Disease Classification

Wafaa H. Alwan; Sabah M. Alturfi

doi:10.32604/csse.2025.064195

January 1, 2025Computer Systems Science and EngineeringOpen Access

Multi-Stage Vision Transformer and Knowledge Graph Fusion for Enhanced Plant Disease Classification

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Key Points

This research aims to improve diagnostic systems for plant diseases through a hybrid framework that integrates vision transformers and knowledge graphs.
Developed a multi-stage vision transformer architecture.
Integrated a knowledge graph to enhance classification accuracy.
Evaluated the framework using various plant disease datasets.
Achieved significant improvements in classification accuracy compared to traditional methods.
Demonstrated enhanced diagnostic capabilities under diverse conditions.

Implication

Novel hybrid framework enhances plant disease classification, indicating improved diagnostic systems for agriculture.

Abstract

Plant diseases pose a significant challenge to global agricultural productivity, necessitating efficient and precise diagnostic systems for early intervention and mitigation. In this study, we propose a novel hybrid framework... | Find, read and cite all the research you need on Tech Science Press

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Cite This Study

Alwan et al. (2025) studied this question.

synapsesocial.com/papers/6a201a06c1b320180d0def9c https://doi.org/10.32604/csse.2025.064195

View Full Paper

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Multi-Stage Vision Transformer and Knowledge Graph Fusion for Enhanced Plant Disease Classification

Key Points

Implication

Abstract

Discussion

Cite This Study

Multi-Stage Vision Transformer and Knowledge Graph Fusion for Enhanced Plant Disease Classification

Key Points

Implication

Abstract

Discussion

Cite This Study

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