Grounding DINO and distillation-enhanced model for advanced traffic sign detection and classification in autonomous vehicles

Accurate traffic sign detection is critical for safe autonomous driving. This paper presents a novel approach that integrates GroundingDINO, known for its semantic grounding capabilities, with a self-distilled ResNet to enhance detection performance and real-time feasibility. While GroundingDINO exc...

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Hlavní autoři:	Hoang Ngoc Tran, Nam Nhat Ngo Nguyen, Nhi Quynh Phan Le, Thu Anh Ngoc Le, Anh Duy Nguyen
Médium:	Artigo
Jazyk:	Inglês
Vydáno:	Elsevier 2025-04-01
Edice:	Engineering Science and Technology, an International Journal
Témata:	Traffic sign recognition Lightweight models Open-set object detection Self-distillation Model compression Grounding DINO
On-line přístup:	http://www.sciencedirect.com/science/article/pii/S2215098625000837
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