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Titlebook: Human Face Recognition Using Third-Order Synthetic Neural Networks; Okechukwu A. Uwechue,Abhijit S. Pandya Book 1997 Springer Science+Busi

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發(fā)表于 2025-3-23 13:46:59 | 只看該作者
The Springer International Series in Engineering and Computer Sciencehttp://image.papertrans.cn/h/image/429153.jpg
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發(fā)表于 2025-3-23 16:46:18 | 只看該作者
978-1-4613-6832-8Springer Science+Business Media New York 1997
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發(fā)表于 2025-3-23 21:03:01 | 只看該作者
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發(fā)表于 2025-3-23 22:51:21 | 只看該作者
Introduction, be applied to the related task of . pattern recognition typically by paying the high cost of very large training sets and very long training times. The objective of this book is to explore the viability of the application of . synthetic neural network technology to transformation-invariant recognit
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發(fā)表于 2025-3-24 03:23:54 | 只看該作者
Face Recognition,ance with speech recognition systems etc. Face recognition is important to humans, and the face plays a major role in social intercourse, conveying emotions and feelings. Humans are very adept at recognising faces and can do so with ease even under a range of different physical conditions. However,
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發(fā)表于 2025-3-24 06:52:43 | 只看該作者
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發(fā)表于 2025-3-24 12:58:46 | 只看該作者
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發(fā)表于 2025-3-24 16:45:31 | 只看該作者
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發(fā)表于 2025-3-24 21:05:31 | 只看該作者
Network Training, presents input patterns to the network, compares the resulting outputs with those desired, and then adjusts the network weights accordingly in order to reduce the difference. Unsupervised training requires no’ teacher’: input patterns are applied and the network selforganises by updating its weight
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發(fā)表于 2025-3-25 02:22:36 | 只看該作者
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