Helmet Detection and Number Plate Recognition Using YOLOv8 and Tensorflow Algorithm in Machine Learning

Dipti Prajapati; Samishtarani Sabat; Sanika Bhilare; Rashmi Vishe; Prof. Suman Bhujbal

doi:10.55524/ijircst.2024.12.2.16

Abstract

In many suburbs, urban areas and locals across the globe there is a disconcerting surge in motorcycle accidents has become increasingly evident. Even though a helmet is the most important safety gadget, people do not wear it. Yet helmets stand as indispensable guardians shielding riders from the ravages of head injuries, an all-too-common occurrence in the chaotic landscape of accidents. People even knowing the importance of helmet ignore wearing them, which prone to accidents causing head injuries and elevate the collective standard of road safety therefore it is incumbent upon both the governing bodies and individual riders alike to vigorously champion and enforce the unwavering and meticulous utilization of helmets as an inseparable facet of conscientious motorcycle navigation.

Keywords

Intrusion detection, K-NN, Naïve - Bayes

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Cites this article as

D. Prajapati, S. Sabat, S. Bhilare, R. Vishe, P. S. Bhujbal, "Helmet Detection and Number Plate Recognition Using YOLOv8 and Tensorflow Algorithm in Machine Learning ", International Journal of Innovative Research in Computer Science and Technology (IJIRCST), Vol-12, no.2, pp.91-95, 2024. Available from: https://doi.org/10.55524/ijircst.2024.12.2.16

Corresponding Author

Dipti Prajapati

Student, Department of Computer Science and Engineering, University of Mumbai, Thane, India

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