Human Face Recognition Using Third-Order Synthetic Neural Networks

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.

שנה

1997

שפה

English

סדרה

The Springer International Series in Engineering and Computer Science, Multimedia Systems and Applications -- 410

הוצאה

Springer US

מהדורות

1

עמודים

123

ISBN

9781461368328

מקור הנתונים: Wikidata