Yahia Said1,*, Yahya Alassaf2, Refka Ghodhbani3, Yazan Ahmad Alsariera4, Taoufik Saidani3, Olfa Ben Rhaiem4, Mohamad Khaled Makhdoum1, Manel Hleili5
CMES-Computer Modeling in Engineering & Sciences, Vol.141, No.1, pp. 733-749, 2024, DOI:10.32604/cmes.2024.052369
Abstract Enhancing road safety globally is imperative, especially given the significant portion of traffic-related fatalities attributed to motorcycle accidents resulting from non-compliance with helmet regulations. Acknowledging the critical role of helmets in rider protection, this paper presents an innovative approach to helmet violation detection using deep learning methodologies. The primary innovation involves the adaptation of the PerspectiveNet architecture, transitioning from the original Res2Net to the more efficient EfficientNet v2 backbone, aimed at bolstering detection capabilities. Through rigorous optimization techniques and extensive experimentation utilizing the India driving dataset (IDD) for training and validation, the system demonstrates exceptional More >
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