Classification of Grapevine Leaf Types with Vision Transformer Architecture DOI Open Access
Esra Kavalcı Yılmaz, Hatice Aktaş, Kemal Adem

et al.

Cumhuriyet Science Journal, Journal Year: 2024, Volume and Issue: 45(4), P. 701 - 706

Published: Dec. 13, 2024

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

Language: Английский

A multi-frequency feature extraction and sparse attention mechanism integrated Mamba model for lithium-ion battery state of health estimation DOI
Hai‐Kun Wang, M. Gao, X. C. Dai

et al.

Journal of Energy Storage, Journal Year: 2025, Volume and Issue: 123, P. 116643 - 116643

Published: May 1, 2025

Language: Английский

Citations

0
Research and Analysis of the Application of Machine Learning in Agricultural Development DOI Creative Commons

Yimin Yuan

Transactions on Computer Science and Intelligent Systems Research, Journal Year: 2024, Volume and Issue: 5, P. 1035 - 1042

Published: Aug. 12, 2024

Agriculture is the most basic, fundamental and important industry. Now, amid global climate change resource shortages, agriculture must deal with challenges of growing demand as world's population increases This article organizes three aspects that need improvement: anticipatory preparation before production, improvement production methods, detection classification agricultural products, analyzes how machine learning can help progress in these aspects. Residual deep convolution spatial pyramid pooling algorithms be used to detect plant pests diseases. The RF algorithm, XGBoost LightGBM algorithm CatBoos generate landslide susceptibility maps. Deep learning, convolutional neural networks, support vector machines identify hybrid wheat. Through this research, it determined great development, development mutual. significance study lies face problems.

Language: Английский

Citations

0
Classification of Grapevine Leaf Types with Vision Transformer Architecture DOI Open Access
Esra Kavalcı Yılmaz, Hatice Aktaş, Kemal Adem

et al.

Cumhuriyet Science Journal, Journal Year: 2024, Volume and Issue: 45(4), P. 701 - 706

Published: Dec. 13, 2024

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

Language: Английский

Citations

0