Self-supervised few-shot learning for real-time traffic sign classification

Although supervised approaches for traffic sign classification have demonstrated excellent performance, they are limited to classifying several traffic signs defined in the training dataset. This prevents them from being applied to different domains, i.e., different countries. Herein, we propose a s...

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Autors principals:	Anh-Khoa Tho Nguyen, Tin Tran, Phuc Hong Nguyen, Vinh Quang Dinh
Format:	Artigo
Idioma:	Inglês
Publicat:	Universitas Ahmad Dahlan 2024-02-01
Col·lecció:	IJAIN (International Journal of Advances in Intelligent Informatics)
Matèries:	traffic sign classification one-shot learning few-shot learning self-supervised learning clip-based approach
Accés en línia:	http://ijain.org/index.php/IJAIN/article/view/1522
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