Classification of Grapevine Leaf Types with Vision Transformer Architecture

Esra Kavalcı Yılmaz; Hatice Aktaş; Kemal Adem

doi:10.17776/csj.1548189

EN

Classification of Grapevine Leaf Types with Vision Transformer Architecture

Abstract

Viticulture plays an important role in agriculture. Farmers prefer grapevine cultivation because not only its fruit but also its leaves are used in various fields. Both the use and trade of grapevine leaves within the country is an important source of income. Grapevine leaves, which are grown in almost all countries and used as edible, vary in terms of species. Determining and cultivating the species according to their suitability in terms of productivity is important. In this study, artificial intelligence methods were used to classify grapevine leaf species. The dataset consisting of five different classes, including 100 grapevine leaf images for each class, totalling 500 images, was classified using ViT, VGG19 and MobileNet methods. When the methods used in this study to help increase productivity in production are evaluated, ViT method has the best accuracy rate with 94%.

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References

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Details

Primary Language

English

Subjects

Plant Biotechnology

Journal Section

Research Article

Authors

Esra Kavalcı Yılmaz ^*
0000-0003-1314-4495
Türkiye

Hatice Aktaş
0000-0002-1104-9307
Türkiye

Kemal Adem
0000-0002-3752-7354
Türkiye

Publication Date

December 30, 2024

Submission Date

September 11, 2024

Acceptance Date

December 13, 2024

Published in Issue

Year 2024 Volume: 45 Number: 4

DOI

https://doi.org/10.17776/csj.1548189

IZ

https://izlik.org/JA44FK29KA

Cite

RIS / Bibtex

APA

Kavalcı Yılmaz, E., Aktaş, H., & Adem, K. (2024). Classification of Grapevine Leaf Types with Vision Transformer Architecture. Cumhuriyet Science Journal, 45(4), 701-706. https://doi.org/10.17776/csj.1548189

Cited By

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

Applied Fruit Science

https://doi.org/10.1007/s10341-026-01780-w

Classification of Grapevine Leaf Types with Vision Transformer Architecture

Abstract

Keywords

Öz

References

Details

Primary Language

Subjects

Journal Section

Authors

Publication Date

Submission Date

Acceptance Date

Published in Issue

DOI

IZ

Cite

Cited By

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