Abstract
The application of computer vision analysis technology based on traditional image analysis and machine learning techniques in the field of vehicle detection is the focus of this paper. This paper fills the gap in previous research and provides a comprehensive overview and comparison of vehicle detection models based on computer vision analysis. This paper first briefly outlines the goals of vehicle recognition, evaluation indicators of models, and widely used datasets; then, it summarizes vehicle detection models based on traditional image processing techniques and machine learning techniques. Finally, the advantages and disadvantages of various models and sensors are discussed, and potential future development directions are proposed.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
