Abstract
AbstractWith the advancement of video target positioning technology, the amount of image data captured by people is increasing rapidly, which puts forward more efficient and automated requirements for data processing methods. As the most popular artificial intelligence technology, deep intelligence has become a research hotspot and has shown potential in the field of mobile image target search. This paper focuses on the research of track and field image target detection based on feature learning. Aiming at some of the problems in video target detection, we use feature learning to solve related problems, so as to improve the accuracy of target detection, and carry out experimental verification. As a result, the target detection method based on feature learning proposed in this paper is 5% more accurate than the traditional target detection method.KeywordsFeature learningTarget detectionTrack and field videoSports video
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.
