NDLI: Two classifiers based on nearest feature plane for recognition

Content Provider	IEEE Xplore Digital Library
Author	Qingxiang Feng Jeng-Shyang Pan Lijun Yan
Copyright Year	2013
Description	Author affiliation: Shenzhen Grad. Sch., Dept. of Comput. Sci. & Technol., Harbin Inst. of Technol., Shenzhen, China (Qingxiang Feng; Jeng-Shyang Pan; Lijun Yan)
Abstract	In this paper, two improved methods based on nearest feature plane (NFP), called as center-based nearest feature plane (CNFP) and line-based nearest feature plane (LNFP), are proposed for recognition. Borrowing the concept from the nearest neighbor plane (NNP) classifier and center-based nearest neighbor (CNN) classifier, the proposed methods choose the valuable representation of the class to reduce the computational complexity of NFP. At the same time, CNFP and LNFP try their best to get the better performance than NFP classifier. A large number of experiments on Yale face database and soil object database are used to evaluate the proposed algorithms. The experimental result demonstrate that the proposed method take lower computational complexity and achieve better recognition rate than the other improved classifiers.
Starting Page	3216
Ending Page	3219
File Size	286762
Page Count	4
File Format	PDF
ISBN	9781479923410
DOI	10.1109/ICIP.2013.6738662
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2013-09-15
Publisher Place	Australia
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Nearest Feature Plane Face Recognition Object Recognition
Content Type	Text
Resource Type	Article

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