Student Physical Violence Detection using Convolutional Neural Networks

John Clement Suladay Escobanez, B. Comendador
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引用次数: 2

Abstract

Physical bullying has been an evident issue in the Philippines and Global Context. Thus, it was widely recognized as a major threat in the younger generation in almost every country in the world. It includes wide variety of acts and contexts. As worst reality, physical violence happens mostly in schools. As a result, it affects a person not only physically but also mentally that even leads to death. Nowadays, numerous research in action recognition has been done through Machine Learning to provide an assistance in predicting and recognizing actions using cameras. In this paper, the researcher utilized machine learning algorithms such as Convolutional Neural Networks to train and recognize actions of physical bullying such as Kicking, Punching, and Head Hitting. The findings revealed a positive result in detecting such actions using Convolutional Neural Networks. With such, it enables the prevention of further physical bullying occurrences in the future using CCTV Cameras.
使用卷积神经网络检测学生身体暴力
在菲律宾和全球范围内,身体欺凌一直是一个明显的问题。因此,它被广泛认为是世界上几乎每个国家年轻一代的主要威胁。它包括各种各样的行为和语境。最糟糕的现实是,身体暴力大多发生在学校。因此,它不仅影响一个人的身体,也影响一个人的精神,甚至导致死亡。如今,许多关于动作识别的研究都是通过机器学习来帮助预测和识别使用相机的动作。在本文中,研究人员利用卷积神经网络等机器学习算法来训练和识别身体欺凌的行为,如踢、打、撞头。研究结果显示,卷积神经网络在检测此类行为方面取得了积极的成果。这样,它可以防止未来使用闭路电视摄像机发生进一步的身体欺凌事件。
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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