Human and Object Detection using Machine Learning Algorithm

Md. Tabil Ahammed, Sudipto Ghosh, Md. Ashikur Rahman Ashik
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引用次数: 5

Abstract

Films with abandoned objects may be identified and traced using this paper’s technique. Especially in high-traffic locations like railway stations and airports, unattended baggage poses a severe security risk. By using the power of deep learning, people and their belongings may be accurately recognized. Each photograph is accompanied by a training video that comprises more than 18,000 people and their baggage (such as backpacks and purses). The YOLOv3 model is used, which has a real-time accuracy of 98 percent. Determine who owns something and if it has been abandoned. People and their luggage may be studied using an approach that takes into account their location and travel patterns. 65.66% of the time, abandoned properties and their owners are correctly identified 65.10% of the time, ownership is also correctly identified.
使用机器学习算法的人和物体检测
使用本文的技术可以识别和追踪带有废弃物体的电影。特别是在火车站和机场等人流密集的地方,无人看管的行李会带来严重的安全风险。通过使用深度学习的力量,可以准确地识别人和他们的财物。每张照片都配有一段培训视频,其中包括1.8万多人及其行李(如背包和钱包)。采用YOLOv3模型,实时精度达98%。确定谁拥有某样东西,以及它是否已被遗弃。人们和他们的行李可以使用一种考虑到他们的位置和旅行模式的方法来研究。65.66%的时候,被遗弃的财产及其所有者被正确识别。65.10%的时候,所有权也被正确识别。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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