Augmenting the Robustness and Efficiency of Violence Detection Systems for Surveillance and Non-Surveillance Scenarios-Reference-Cited by-同舟云学术

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Augmenting the Robustness and Efficiency of Violence Detection Systems for Surveillance and Non-Surveillance Scenarios

Published:2023 Issue: Volume:11 Page:123295-123313
ISSN:2169-3536
Container-title:IEEE Access
language:
Short-container-title:IEEE Access

Author:

Shoaib Muhammad¹^ORCID,Ullah Asad¹,Abbasi Irshad Ahmed²^ORCID,Algarni Fahad³^ORCID,Khan Adnan Shahid²^ORCID

Affiliation:

1. Department of Computer Science and Information Technology, Sarhad University of Science and Information Technology, Peshawar, Pakistan

2. Faculty of Computer Science and Information Technology, Universiti Malaysia Sarawak, Kota Samarahan, Malaysia

3. Faculty of Computing and Information Technology, University of Bisha, Bisha, Saudi Arabia

Funder

Deanship of Scientific Research at the University of Bisha through the Fast-Track Research Support Program

Universiti Malaysia Sarawak, Malaysia

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

General Engineering,General Materials Science,General Computer Science,Electrical and Electronic Engineering

Link

http://xplorestaging.ieee.org/ielx7/6287639/10005208/10304142.pdf?arnumber=10304142

Reference59 articles.

1. An Overview of Deep Learning Based Methods for Unsupervised and Semi-Supervised Anomaly Detection in Videos

2. Bus Violence: An Open Benchmark for Video Violence Detection on Public Transport

3. A survey of single-scene video anomaly detection;ramachandra;IEEE Trans Pattern Anal Mach Intell,2022

4. Violence Detection Using Spatiotemporal Features with 3D Convolutional Neural Network

5. Artificial Intelligence of Things-assisted two-stream neural network for anomaly detection in surveillance Big Video Data

Cited by 1 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. A spatio-temporal model for violence detection based on spatial and temporal attention modules and 2D CNNs;Pattern Analysis and Applications;2024-04-24

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