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Title	Opportunities And Challenges Of Yolo -World In Smart City Surveillance
ID_Doc	40259
Authors	Yang Q.; Song L.; Zhou H.
Year	2024
Published	Proceedings - 2024 2nd International Conference on Mechatronics, IoT and Industrial Informatics, ICMIII 2024
DOI	http://dx.doi.org/10.1109/ICMIII62623.2024.00026
Abstract	This study investigates the opportunities and challenges of the YOLO-World model in the context of smart city surveillance. It offers a comprehensive examination of the benefits and obstacles posed by this pioneering cross-modal object detection technology in the smart city surveillance landscape. The YOLO-World model, underpinned by its innovative RepVL-PAN architecture, achieves a sophisticated fusion of visual and linguistic data, propelling surveillance technology to new heights of intelligence and contextual understanding. This evolution transcends traditional object recognition, empowering smart monitoring systems with the ability to decipher and interpret intricate scenarios, thereby enabling real-time responsiveness, precise identification, and deep scene comprehension. These enhancements significantly enhance urban safety measures and aid in optimizing traffic flow. In summary, YOLO-World ushers in new possibilities for smart city surveillance, demonstrating substantial potential in enhancing the efficiency and safety of urban management. Yet, realizing this potential necessitates overcoming dual hurdles in both technological advancement and socio-ethical considerations. Future research should focus on the synergistic evolution of technological refinement and legal frameworks, ensuring that technological progress aligns harmoniously with societal needs. © 2024 IEEE.
Author Keywords	cross-modal object detection technology; smart city; surveillance technology; visual-linguistic fusion; YOLO-world

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