|
|||||||||||||||
|
INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT International Peer Reviewed & Refereed Journals, Open Access Journal ISSN Approved Journal No: 2456-4184 | Impact factor: 8.76 | ESTD Year: 2016 Scholarly open access journals, Peer-reviewed, and Refereed Journals, Impact factor 8.76 (Calculate by google scholar and Semantic Scholar | AI-Powered Research Tool) , Multidisciplinary, Monthly, Indexing in all major database & Metadata, Citation Generator, Digital Object Identifier(DOI) |
||||||||||||||
Issue: May 2024
Volume 9 | Issue 5
Review Result and Publication of Paper within : 2-3 days
Click Here For more DetailsFor Authors
Forms / Download
Published Issue Details
Editorial Board
Other IMP Links
Facts & Figure
Impact Factor : 8.76
Issue per Year : 12
Volume Published : 9
Issue Published : 96
Article Submitted :
Article Published :
Total Authors :
Total Reviewer :
Total Countries :
Indexing Partner
Join RMS/Earn 300
Licence
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License
|
Published Paper Details
|
|
| Paper Title: | Transformative solution for violence identification |
| Authors Name: | Venkatachalam G |
| Download E-Certificate: | Download |
| Author Reg. ID: |
IJNRD_216578
|
| Published Paper Id: | IJNRD2404574 |
| Published In: | Volume 9 Issue 4, April-2024 |
| DOI: | |
| Abstract: | The average yearly death toll from acts of human aggression worldwide is 7.9 per 10,000 individuals. The majority of these acts of violence against people occur suddenly or in remote places.One of the most interesting and difficult study areas in computer vision is violence recognition. Finding violence using surveillance cameras in public and private spaces is one of its unique uses. We demand that these violent incidents be immediately under control. They must conduct a thorough search for automated violence detection systems because human operators are required to monitor the surveillance video screen, which frequently results in mistakes and neglects to identify the occurrence of unexpected events. One of the main obstacles to halting these activities is the information delay in this case. In this work, the detecting technique is employed to thrive on this issue. One of the best computer vision algorithms is the one that uses CCTV to detect moving things. These days, CCTV cameras are installed on every street and are quite useful for case solving. Certain deep learning algorithms are applied in computer vision to anticipate and identify actions and attributes in videos. When police arrive at dangerous locations in real time, they analyse CCTV footage and begin an investigation before moving further. The purpose of this study is to consciously identify violent crimes seen on CCTV. Several uses for gathered video features are made possible by the use of computer vision and machine learning techniques, one of which is safety monitoring. The effectiveness of violent event detection is determined by how accurate and efficient it is. We describe a unique architecture for video surveillance camera-based violence detection in this study. The Yolo v8 models identify the usage of weapons in the incident, as well as the violent act. These deep learning models constitute the basis of the work and are utilised to create a video detection system. Real-time software or an application programming interface (API) can be created using this concept. According to the study's findings, the suggested model has a 74% accuracy |
| Keywords: | Closed-circuit television (CCTV), Human violence, deep learning, Machine learning, Transfer learning. |
| Cite Article: | "Transformative solution for violence identification", International Journal of Novel Research and Development (www.ijnrd.org), ISSN:2456-4184, Vol.9, Issue 4, page no.f605-f612, April-2024, Available :http://www.ijnrd.org/papers/IJNRD2404574.pdf |
| Downloads: | 00022 |
| ISSN: |
2456-4184 | IMPACT FACTOR: 8.76 Calculated By Google Scholar| ESTD YEAR: 2016 An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.76 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator |
| Publication Details: |
Published Paper ID:IJNRD2404574 Registration ID: 216578 Published In: Volume 9 Issue 4, April-2024 DOI (Digital Object Identifier): Page No: f605-f612 Country: Coimbatore, Tamil nadu, India Research Area: Computer Science & Technology Publisher : IJ Publication Published Paper URL : https://www.ijnrd.org/viewpaperforall?paper=IJNRD2404574 Published Paper PDF: https://www.ijnrd.org/papers/IJNRD2404574 |
| Share Article: |
|
|
Click Here to Download This Article |
|
| Article Preview | |
|
|
|
Major Indexing from www.ijnrd.org
| Semantic Scholar | Microsaoft Academic | ORCID | Zenodo |
| Google Scholar | ResearcherID Thomson Reuters | Mendeley : reference manager | Academia.edu |
| arXiv.org : cornell university library | Research Gate | CiteSeerX | PUBLON |
| DRJI | SSRN | Scribd | DocStoc |
ISSN Details
 |
 |
|
ISSN: 2456-4184
Impact Factor: 8.76 and ISSN APPROVED
Journal Starting Year (ESTD) : 2016
DOI (A digital object identifier)
Conference
Open Access License Policy
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License
Important Details
Social Media
Licence
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License
Join RMS/Earn 300
| Copyright © 2024 - All Rights Reserved - IJNRD |
Facebook Twitter Instagram LinkedIn