Face Recognition with Quantum Associative Networks Using Overcomplete Gabor Wavelet

被引：7
|
作者：
Tay, Nuo Wi [1 ]
Loo, Chu Kiong [1 ]
Perus, Mitja [2 ]
机构：
[1] Multimedia Univ, Fac Informat Sci & Technol, Melaka, Malaysia
[2] Univ Ljubljana, Lab Cognit Modeling, FRI, Ljubljana, Slovenia
来源：
COGNITIVE COMPUTATION | 2010年 / 2卷 / 04期
关键词：
Quantum Holography; Gabor wavelet; Information maximization; Invariance; Face recognition; OBJECT-RECOGNITION; RECEPTIVE-FIELDS; VISUAL-CORTEX; INFORMATION; SIGNALS; IMAGES; CELLS; MODEL;
D O I：
10.1007/s12559-010-9047-2
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
Gabor wavelet is considered the best mathematical descriptor for receptive fields in the striate cortex. Besides, as a basis function, it is suitable to sparsely represent natural scenes due to its property in maximizing information. It is argued that Gabor-like receptive fields are emerged by sparseness-enforcing or infomax method. In this paper, we incorporate Gabor overcomplete representation into quantum holography for image recognition tasks, with suggestions in improvements through iterative method for reconstruction.
引用
收藏
页码：297 / 302
页数：6
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