PMID- 24657572
OWN - NLM
STAT- MEDLINE
DCOM- 20150512
LR  - 20191210
IS  - 1879-2782 (Electronic)
IS  - 0893-6080 (Linking)
VI  - 54
DP  - 2014 Jun
TI  - Stable locality sensitive discriminant analysis for image recognition.
PG  - 49-56
LID - S0893-6080(14)00050-1 [pii]
LID - 10.1016/j.neunet.2014.02.009 [doi]
AB  - Locality Sensitive Discriminant Analysis (LSDA) is one of the prevalent 
      discriminant approaches based on manifold learning for dimensionality reduction. 
      However, LSDA ignores the intra-class variation that characterizes the diversity 
      of data, resulting in unstableness of the intra-class geometrical structure 
      representation and not good enough performance of the algorithm. In this paper, a 
      novel approach is proposed, namely stable locality sensitive discriminant 
      analysis (SLSDA), for dimensionality reduction. SLSDA constructs an adjacency 
      graph to model the diversity of data and then integrates it in the objective 
      function of LSDA. Experimental results in five databases show the effectiveness 
      of the proposed approach.
CI  - Copyright (c) 2014 Elsevier Ltd. All rights reserved.
FAU - Gao, Quanxue
AU  - Gao Q
AD  - State Key Laboratory of Integrated Services Networks, Xidian University, Xi'an, 
      China. Electronic address: qxgao@xidian.edu.cn.
FAU - Liu, Jingjing
AU  - Liu J
AD  - State Key Laboratory of Integrated Services Networks, Xidian University, Xi'an, 
      China.
FAU - Cui, Kai
AU  - Cui K
AD  - State Key Laboratory of Integrated Services Networks, Xidian University, Xi'an, 
      China.
FAU - Zhang, Hailin
AU  - Zhang H
AD  - State Key Laboratory of Integrated Services Networks, Xidian University, Xi'an, 
      China.
FAU - Wang, Xiaogang
AU  - Wang X
AD  - Department of Electronic Engineering, The Chinese University of Hong Kong, Hong 
      Kong.
LA  - eng
PT  - Journal Article
PT  - Research Support, Non-U.S. Gov't
DEP - 20140304
PL  - United States
TA  - Neural Netw
JT  - Neural networks : the official journal of the International Neural Network 
      Society
JID - 8805018
SB  - IM
MH  - Algorithms
MH  - Databases, Factual
MH  - *Discriminant Analysis
MH  - *Models, Theoretical
MH  - Pattern Recognition, Automated/*methods
MH  - Recognition, Psychology
OTO - NOTNLM
OT  - Dimensionality reduction
OT  - Diversity
OT  - Manifold learning
OT  - Similarity
EDAT- 2014/03/25 06:00
MHDA- 2015/05/13 06:00
CRDT- 2014/03/25 06:00
PHST- 2012/07/26 00:00 [received]
PHST- 2013/12/27 00:00 [revised]
PHST- 2014/02/21 00:00 [accepted]
PHST- 2014/03/25 06:00 [entrez]
PHST- 2014/03/25 06:00 [pubmed]
PHST- 2015/05/13 06:00 [medline]
AID - S0893-6080(14)00050-1 [pii]
AID - 10.1016/j.neunet.2014.02.009 [doi]
PST - ppublish
SO  - Neural Netw. 2014 Jun;54:49-56. doi: 10.1016/j.neunet.2014.02.009. Epub 2014 Mar 
      4.