Predicting public assault incidents through AI-enabled human activity recognition-Reference-Cited by-同舟云学术

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Predicting public assault incidents through AI-enabled human activity recognition

Published:2023-12-08 Issue: Volume:57 Page:1-8
ISSN:
Container-title:2023 Fourth International Conference on Smart Technologies in Computing, Electrical and Electronics (ICSTCEE)
language:
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Author:

P Rahul¹,S Rubin Bose²,R Regin¹,M Nishanth¹,P Roshan¹,Dhilip Reshma³

Affiliation:

1. SRM Institute of Science and Technology,Department of Computer Science and Engineering,Ramapuram,Chennai,India

2. SRM Institute of Science and Technology,Department of Electronics and Communication Engineering,Ramapuram,Chennai,India

3. SRM Easwari Engineering College,Department of Information Technology,Ramapuram,Chennai,India

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx8/10584833/10584835/10584991.pdf?arnumber=10584991

Reference14 articles.

1. InnoHAR: A deep neural network for complex human activity recognition;Xu,2019

2. An Intelligent Non-Invasive Real-Time Human Activity Recognition System for Next-Generation Healthcare

3. Deep-Learning-Enhanced Human Activity Recognition for Internet of Healthcare Things

4. Predict & cluster: Unsupervised skeleton based action recognition;Su

5. VLA

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