人体活动识别研究进展

Jigar Shah, M. S. Shaikh, Samir Patel
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引用次数: 4

摘要

人类活动识别和预测是目前人工智能和机器学习的少数先进应用之一。HAR用于医疗辅助系统,安全监控,游戏行业等。在本文中,我们着眼于这一领域的挑战,并试图获得HAR架构的全面知识。我们还比较了不同的机器学习技术,如支持向量机,Naïve贝叶斯,随机森林,隐马尔可夫模型,卷积神经网络等,不同的数据集已经从各种传感器,相机,陀螺仪,加速度计等。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A Review on Human Activity Recognition
Human activity recognition(HAR) and the forecast is nowadays among the few advance application of AI and machine learning. HAR is used in Healthcare assistance systems, Security surveillance, gaming industries etc. In this paper, we look into challenges in this field and also try to get thorough knowledge of HAR architecture. We also compared different machine learning techniques like Support Vector Machine, Naïve Bayes, Random Forest, Hidden Markov model, Convolution neural network, etc. different Datasets have been taken from various sensors, camera, gyroscope, accelerometer etc.
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