Abstract
Pattern detection problems require a separation between two classes, Target and Clutter, where the probability of the former is substantially smaller compared to that of the latter. In this paper we propose a new classifier that exploits this property, yielding a low complexity yet effective target detection algorithm. This algorithm, called the maximal rejection classifier (MRC), is based on linear successive rejection operations. An application of detecting faces in images is demonstrated using the MRC with encouraging results.
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.
