Advanced Systems for Detecting and Recognizing Traffic Objects

Gaurav Singh and Sonam Singh

International Journal of Scientific Research in Computer Science, Engineering and Information Technology, 2024, vol. 10, issue 4, 87-94

Abstract: Traffic object detection and recognition systems have become critical components in the advancement of intelligent transportation systems (ITS). These systems leverage various technologies such as computer vision, machine learning, and sensor fusion to accurately identify and classify objects on the road, including vehicles, pedestrians, traffic signs, and obstacles. The integration of these technologies enhances traffic management, improves road safety, and facilitates the development of autonomous vehicles. This paper provides an overview of the state-of-the-art methods and technologies used in traffic object detection and recognition. It also discusses the challenges faced in real-world implementations, such as varying weather conditions, lighting changes, and occlusions, and explores potential solutions and future research directions to address these issues.

Keywords: Object Detection; Convolutional Neural Network; Deep Learning; Machine Learning; GSM; GPS; Google Maps; Tracking System (search for similar items in EconPapers)
Date: 2024
Note: Article URL: https://ijsrcseit.com/home/article/view/CSEIT24104111
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Persistent link: https://EconPapers.repec.org/RePEc:jbh:ijsrcs:v10:y2024:i4:id:261

DOI: 10.32628/CSEIT24104111

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