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

页码：297 / 302

页数：6

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