A hybrid CNN and LSTM-based deep learning model for abnormal behavior detection
Author:
Publisher
Springer Science and Business Media LLC
Subject
Computer Networks and Communications,Hardware and Architecture,Media Technology,Software
Link
https://link.springer.com/content/pdf/10.1007/s11042-021-11887-9.pdf
Reference57 articles.
1. Aliet S, Shah M (2010) Human action recognition in videos using kinematic features and multiple instance learning. IEEE Trans Pattern Anal Mach Intell 32(2):288–303
2. Alwan M et al (2006) A smart and passive floor-vibration based fall detector for elderly. In: 2nd International Conference on Information and Communication Technologies
3. Arifoglu D, Bouchach A (2017) Activity recognition and abnormal behaviour detection with recurrent neural networks. In: Proc. of MobiSPC. pp 86–93
4. Belshaw M, Taati B, Giesbercht D, Mihailidis A (2011) Intelligent vision-based fall detection system: preliminary results from a real world deployment. RESNA/ICTA 2011: Advancing Rehabilitation Technologies for an Aging Society
5. Belshaw M, Taati B, Snoek J, Mihailidis A (2011) Towards a single sensor passive solution for automated fall detection. Conf Proc IEEE Eng Med Biol Soc. pp 1773–1776
Cited by 22 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献
1. The use of convolutional neural networks for abnormal behavior recognition in crowd scenes;Information Processing & Management;2025-01
2. Deep Learning for Identification of Behavioral Changes;Advances in Finance, Accounting, and Economics;2024-10-25
3. Enhancing public safety: a hybrid Conv_Trans-OptBiSVM approach for real-time abnormal behavior detection in crowded environments;Signal, Image and Video Processing;2024-09-04
4. An effective framework of human abnormal behaviour recognition and tracking using multiscale dilated assisted residual attention network;Expert Systems with Applications;2024-08
5. Advancing predictive maintenance for gas turbines: An intelligent monitoring approach with ANFIS, LSTM, and reliability analysis;Computers & Industrial Engineering;2024-05
1.学者识别学者识别
2.学术分析学术分析
3.人才评估人才评估
"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370
www.globalauthorid.com
TOP
Copyright © 2019-2024 北京同舟云网络信息技术有限公司 京公网安备11010802033243号 京ICP备18003416号-3