May 25, 2022, 1:12 a.m. | Iason Katsamenis, Eleni Eirini Karolou, Agapi Davradou, Eftychios Protopapadakis, Anastasios Doulamis, Nikolaos Doulamis, Dimitris Kalogeras

cs.CV updates on arXiv.org arxiv.org

Substantial progress has been made in the field of object detection in road
scenes. However, it is mainly focused on vehicles and pedestrians. To this end,
we investigate traffic cone detection, an object category crucial for road
effects and maintenance. In this work, the YOLOv5 algorithm is employed, in
order to find a solution for the efficient and fast detection of traffic cones.
The YOLOv5 can achieve a high detection accuracy with the score of IoU up to
91.31%. The …

arxiv cv dataset deep learning detection learning real-time time traffic

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