Automated Detection of Violence in Detached Areas using Hybrid Deep Learning Models: A YOLO-5 and CNN Approach-Reference-Cited by-同舟云学术

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Automated Detection of Violence in Detached Areas using Hybrid Deep Learning Models: A YOLO-5 and CNN Approach

Published:2023-12-11 Issue: Volume:6 Page:1276-1282
ISSN:
Container-title:2023 2nd International Conference on Automation, Computing and Renewable Systems (ICACRS)
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Author:

Gautam Vinay¹,Maheshwari Himani²,Tiwari Raj Gaurang¹,Agarwal Ambuj Kumar³,Trivedi Naresh Kumar¹

Affiliation:

1. Chitkara University Institute of Engineering and Technology, Chitkara University,Punjab,India

2. Graphic Era Hill University,School of Computing,Dehradun,Uttrakhand,India

3. Sharda University,Sharda School of Engineering and Technology,Department of Computer Science and Engineering,Greater Noida,India

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10404046/10404076/10404840.pdf?arnumber=10404840

Reference21 articles.

1. Detection and Classification of Different Weapon Types Using Deep Learning

2. A Deep Learning Based Technique for Anomaly Detection in Surveillance Videos

3. Review Of Violence Detection System Using Deep Learning;Dandage;Int. Research Joumal of Engineering and Technology,2019

4. YOLOv3-MT: A YOLOv3 using multi-target tracking for vehicle visual detection

5. Evaluation of multiple features for violent scenes detection multimedia Tools and Applications;Lam,2016

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