Real Time American Sign Language Detection Using Yolo-v9

Autor:	Imran, Amna, Hulikal, Meghana Shashishekhara, Gardi, Hamza A. A.
Rok vydání:	2024
Předmět:	Computer Science - Computer Vision and Pattern Recognition Computer Science - Artificial Intelligence Computer Science - Machine Learning
Druh dokumentu:	Working Paper
Popis:	This paper focuses on real-time American Sign Language Detection. YOLO is a convolutional neural network (CNN) based model, which was first released in 2015. In recent years, it gained popularity for its real-time detection capabilities. Our study specifically targets YOLO-v9 model, released in 2024. As the model is newly introduced, not much work has been done on it, especially not in Sign Language Detection. Our paper provides deep insight on how YOLO- v9 works and better than previous model. Comment: 11 pages, 13 figures, 1 table
Databáze:	arXiv
Externí odkaz:	http://arxiv.org/abs/2407.17950 Zobrazit plný text záznamu View this record from Arxiv