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

и другие.

Cumhuriyet Science Journal, Год журнала: 2024, Номер 45(4), С. 701 - 706

Опубликована: Дек. 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%.

Язык: Английский

Personalized product recommendation system for e-commerce platforms DOI Creative Commons

Shaik Sameena,

Guntupalli Javali,

Nelavelli Srilakshmi

и другие.

ITM Web of Conferences, Год журнала: 2025, Номер 74, С. 03012 - 03012

Опубликована: Янв. 1, 2025

Due to rapid growth in e-commerce, the interest for customized product recommendation systems has grown a lot with high demands effective models. The attempt is made explore development and evaluation of personalized model using H&M data set. research highlights building up an interaction matrix between user items, generation recommendations suited tastes particular user, hyperparameter tuning better performance. Different techniques have been utilized, including KNNBasic, Non-negative Matrix Factorization (NMF), CoClustering, Singular Value Decomposition (SVD). KNNBasic had root mean square error (RMSE) 0.5022 accuracy 42.00%, NMF showed results RMSE 0.4999 51.50%. Co-Clustering result as 0.5000 was 50.50%. Notably, final SVD ranked very well compared others 0.2261 great 90.40% this experiment, emphasizing importance advanced systems. In these experiments, not only relative efficacy different algorithms evident but also that optimization hyperparameters genuinely contributes increasing predictive precision

Язык: Английский

Процитировано

0
Predictive model for customer satisfaction analytics in E-commerce sector using machine learning and deep learning DOI Creative Commons
Hoanh-Su Le,

Thao-Vy Huynh,

Minh Nguyen

и другие.

International Journal of Information Management Data Insights, Год журнала: 2024, Номер 4(2), С. 100295 - 100295

Опубликована: Окт. 7, 2024

Язык: Английский

Процитировано

1
Intelligent Prediction of Cross-Border E-Commerce Customer Satisfaction Using Deep Learning Embeddings DOI Creative Commons
Chunrong Guo, Xiaodong Zhang

IEEE Access, Год журнала: 2024, Номер 12, С. 173268 - 173278

Опубликована: Янв. 1, 2024

Язык: Английский

Процитировано

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

и другие.

Cumhuriyet Science Journal, Год журнала: 2024, Номер 45(4), С. 701 - 706

Опубликована: Дек. 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%.

Язык: Английский

Процитировано

0