Good condition. A copy that has been read but remains intact. May contain markings such as bookplates, stamps, limited notes and highlighting, or a few light stains.

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Bibliographic Details

Title

Human Face Recognition Using Third-Order Synthetic Neural Networks (The Springer International Series in Engineering and Computer Science, 410)

Publisher

Springer

Publication Date

1997

Language

English

ISBN 10

0792399579

ISBN 13

9780792399575

Binding

Hardcover

Condition

Good

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About this title

Synopsis

Human Face Recognition Using Third-Order Synthetic Neural Networks explores the viability of the application of High-order synthetic neural network technology to transformation-invariant recognition of complex visual patterns. High-order networks require little training data (hence, short training times) and have been used to perform transformation-invariant recognition of relatively simple visual patterns, achieving very high recognition rates. The successful results of these methods provided inspiration to address more practical problems which have grayscale as opposed to binary patterns (e.g., alphanumeric characters, aircraft silhouettes) and are also more complex in nature as opposed to purely edge-extracted images - human face recognition is such a problem.
Human Face Recognition Using Third-Order Synthetic Neural Networks serves as an excellent reference for researchers and professionals working on applying neural network technology to the recognition of complex visual patterns.

Synopsis

This text explores the viability of the application of High-order synthetic neural network technology to transformation-invariant recognition of complex visual patterns. High-order networks require little training data (hence, short training times) and have been used to perform transformation-invariant recognition of relatively simple visual patterns, achieving very high recognition rates. The successful results of these methods provided inspiration to address more practical problems which have grayscale as opposed to binary patterns (for example, alphanumeric characters, aircraft silhouettes), and are also more complex in nature as opposed to purely edge-extracted images - human face recognition is such a problem. This text serves as a reference for researchers and professionals working on applying neural network technology to the recognition of complex visual patterns.

"About this title" may belong to another edition of this title.

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