Journal ArticleDOI
Global linear regression coefficient classifier for recognition
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TLDR
A novel classifier based on linear regression classification (LRC) called global linear regression coefficient (GLRC) classifier is proposed for recognition, which achieves better recognition rate than LRC classifier, sparse representation based classification (SRC)classifier, Collaborative representation based classifier and two phase test sample sparse representation (TPTSSR) classifiers and so on.About:
This article is published in Optik.The article was published on 2015-11-01. It has received 3 citations till now. The article focuses on the topics: Quadratic classifier & Margin classifier.read more
Citations
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Journal ArticleDOI
Determination of Customer Satisfaction using Improved K-means algorithm
Hamed Zare,Sima Emadi +1 more
TL;DR: Customer behavioural features—malicious feature—is considered in customer clustering, as well as a method for finding the optimal number of clusters and the initial values of cluster centres to obtain more accurate results, and a method is proposed for modelling their behaviour and extracting knowledge for customer relationship management.
Journal ArticleDOI
A self-adaptive k-means classifier for business incentive in a fashion design environment
TL;DR: In this study, economy is considered as a major liberation in the fashion world by analyzing six attributes, namely, style, color, fabric, brand, price and size that could bring about commercial success.
Journal ArticleDOI
An efficient classification method based on principal component and sparse representation.
Lin Zhai,Shujun Fu,Caiming Zhang,Caiming Zhang,Yunxian Liu,Lu Wang,Guohua Liu,Mingqiang Yang +7 more
TL;DR: An effective fusion of blockwise bi-directional two-dimensional principal component analysis and grouping sparse classification is presented, which has better robustness against position and illumination changes of palmprint images, and can get higher rate of palm print recognition.
References
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Journal ArticleDOI
Nearest neighbor pattern classification
Thomas M. Cover,Peter E. Hart +1 more
TL;DR: The nearest neighbor decision rule assigns to an unclassified sample point the classification of the nearest of a set of previously classified points, so it may be said that half the classification information in an infinite sample set is contained in the nearest neighbor.
Journal ArticleDOI
Eigenfaces vs. Fisherfaces: recognition using class specific linear projection
TL;DR: A face recognition algorithm which is insensitive to large variation in lighting direction and facial expression is developed, based on Fisher's linear discriminant and produces well separated classes in a low-dimensional subspace, even under severe variations in lighting and facial expressions.
Journal ArticleDOI
Robust Face Recognition via Sparse Representation
TL;DR: This work considers the problem of automatically recognizing human faces from frontal views with varying expression and illumination, as well as occlusion and disguise, and proposes a general classification algorithm for (image-based) object recognition based on a sparse representation computed by C1-minimization.
Proceedings ArticleDOI
Sparse representation or collaborative representation: Which helps face recognition?
TL;DR: This paper indicates that it is the CR but not the l1-norm sparsity that makes SRC powerful for face classification, and proposes a very simple yet much more efficient face classification scheme, namely CR based classification with regularized least square (CRC_RLS).
Journal ArticleDOI
Sparse Representation for Computer Vision and Pattern Recognition
TL;DR: This review paper highlights a few representative examples of how the interaction between sparse signal representation and computer vision can enrich both fields, and raises a number of open questions for further study.