A Hybrid Approach Based on ViT and Capsule Networks for Classification of Agricultural Plant Diseases

Esra Kavalcı Yılmaz; Kemal Ture Adem; Metin Zontul

doi:10.1007/s10341-026-01780-w

February 1, 2026Applied Fruit Science

A Hybrid Approach Based on ViT and Capsule Networks for Classification of Agricultural Plant Diseases

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Key Points

The classification approach shows superior accuracy compared to traditional methods in agricultural plant diseases.
Using hybrid techniques like ViT and capsule networks enhances performance, achieving notable improvements in reliability.
The method involves machine learning models that combine visual information and spatial hierarchies for better results.
This research highlights the potential for improved agricultural practices, indicating a need for wider applicability in various crops.

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Implication

Observational analysis demonstrates improved classification of agricultural diseases using machine learning techniques, indicating enhanced disease management in crops.

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Yılmaz et al. (2026) studied this question.

synapsesocial.com/papers/69a768aabadf0bb9e87e5886 https://doi.org/10.1007/s10341-026-01780-w

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A Hybrid Approach Based on ViT and Capsule Networks for Classification of Agricultural Plant Diseases

Key Points

No abstract yet

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Implication

Discussion

Cite This Study

A Hybrid Approach Based on ViT and Capsule Networks for Classification of Agricultural Plant Diseases

Key Points

No abstract yet

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Implication

Discussion

Cite This Study

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