基于RCNN的摩托车头盔自动检测技术

Aliyyah Nur Azhari, W. Wahyono
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引用次数: 0

摘要

由于价格较低,摩托车已成为日常交通工具的热门选择,使其成为高阶层和低阶层市民都能负担得起的交通工具。每个摩托车车主都需要戴头盔,这样骑摩托车的人的头部就可以免受事故的伤害。然而,没有多少人遵守规则,往往不戴头盔,很多人低估了头盔的使用。为此,有必要应用深度学习技术,实现一个可以检测骑手是否戴头盔的系统。本文旨在实现一种深度学习技术,即Faster R - CNN来检测头盔和摩托车手。使用不同的学习率训练400张图像后,平均平均精度(mAP)达到最高,为87%,学习率为0.0001
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Automatic Detection of Helmets on Motorcyclists Using Faster - RCNN
Motorcycles have been a popular choice for a go-to daily means of transportation due to its lower price, making it affordable for high to low-class citizens. Helmets are required for every motorcycle owner so that the rider’s head is protected from accidents. However, not many people follow the rules and tend to not wear helmets and plenty of them underestimate the usage of helmets. For this, it is necessary to implement a system that can detect which rider wears the helmet or not by applying deep learning techniques. This paper aims to implement one of the deep learning techniques, which is Faster R – CNN to detect the helmets and the motorcyclists. After training 400 images using different learning rates, the mean average precision (mAP) achieved the highest with 87% using the learning rate of 0.0001
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