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)
Abstract— Road traffic safety is a crucial concern around the
world, as the number of vehicles on the road increases, so does the
risk of accidents and collisions. Object detection technology has
developed as an effective technique for improving road traffic
safety. This study presents a thorough examination of the most
recent advances in object identification systems and their
applications in road traffic safety. The paper opens by providing
an overview of the issues and risks involved with road traffic,
highlighting the importance of enhanced safety measures. It then
digs into a full review of object identification strategies, ranging
from traditional methods to cutting-edge deep learning models,
demonstrating their capacities to identify vehicles, pedestrians,
cyclists, and other road items.It investigates how these
technologies improve real-time monitoring, collision avoidance,
and traffic management. Furthermore, the article looks into
object detection for traffic law enforcement and monitoring,
emphasizing its significance in improving security and lowering
accidents. It outlines prospective future research directions, such
as the development of powerful, real-time object detection
systems and their application to smart city initiatives.
Keywords— Real-time object detection, road traffic safety,
Bounding boxes,Intersection over Union (IOU), Anchor box, NonMax Suppression.Abstract— Road traffic safety is a crucial concern around the
world, as the number of vehicles on the road increases, so does the
risk of accidents and collisions. Object detection technology has
developed as an effective technique for improving road traffic
safety. This study presents a thorough examination of the most
recent advances in object identification systems and their
applications in road traffic safety. The paper opens by providing
an overview of the issues and risks involved with road traffic,
highlighting the importance of enhanced safety measures. It then
digs into a full review of object identification strategies, ranging
from traditional methods to cutting-edge deep learning models,
demonstrating their capacities to identify vehicles, pedestrians,
cyclists, and other road items.It investigates how these
technologies improve real-time monitoring, collision avoidance,
and traffic management. Furthermore, the article looks into
object detection for traffic law enforcement and monitoring,
emphasizing its significance in improving security and lowering
accidents. It outlines prospective future research directions, such
as the development of powerful, real-time object detection
systems and their application to smart city initiatives.
Keywords:
Keywords— Real-time object detection, road traffic safety, Bounding boxes,Intersection over Union (IOU), Anchor box, NonMax Suppression.
Cite Article:
"Enhancing Road Traffic Safety with YOLO V7 Object Detection", International Journal of Novel Research and Development (www.ijnrd.org), ISSN:2456-4184, Vol.9, Issue 4, page no.a434-a438, April-2024, Available :http://www.ijnrd.org/papers/IJNRD2404056.pdf
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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
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