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Independent component analysis of Gabor features for face recognition
Chengjun Liu
, Harry Wechsler
Research output
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Contribution to journal
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Article
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peer-review
410
Scopus citations
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Dive into the research topics of 'Independent component analysis of Gabor features for face recognition'. Together they form a unique fingerprint.
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Keyphrases
International Cooperative Ataxia Rating Scale (ICARS)
100%
Face Recognition
100%
Gabor Features
100%
Feature-based
63%
Reasoning Model
18%
Face Image
18%
FERET
18%
Probabilistic Reasoning
18%
ORL Dataset
18%
Redundancy
9%
Extraction Methods
9%
Feature Extraction
9%
Pattern Recognition
9%
Principal Coordinate Analysis (PCoA)
9%
Feature Vector
9%
Classification Methods
9%
Local Features
9%
Gabor Wavelet
9%
Gabor
9%
Spatial Locality
9%
Classification Model
9%
Face Recognition Accuracy
9%
Spatial Orientation
9%
Gabor Wavelet Features
9%
Independence Property
9%
Pattern Discrimination
9%
Associative Recall
9%
Orientation Selectivity
9%
Computer Science
Independent Component Analysis
100%
Face Recognition
100%
Gabor feature
100%
Reasoning Model
18%
Probabilistic Reasoning
18%
Feature Extraction
9%
Pattern Recognition
9%
Principal Components
9%
Component Analysis
9%
Feature Vector
9%
Classification Method
9%
local feature
9%
Wavelet Representation
9%
Recognition Accuracy
9%
Spatial Locality
9%
Orientation Selectivity
9%
Engineering
Independent Component Analysis
100%
Face Image
50%
Gabor Wavelet
50%
Dimensionality
25%
Pattern Recognition
25%
Feature Extraction
25%
Principal Components
25%
Component Analysis
25%
Feature Vector
25%
Classification Method
25%
Recognition Accuracy
25%
Earth and Planetary Sciences
Wavelet
100%
Pattern Recognition
50%
Selectivity
50%
Principal Component Analysis
50%
Locale
50%