Advances in pattern recognition systems using neural network technologies
Author(s)
Bibliographic Information
Advances in pattern recognition systems using neural network technologies
（Series in machine perception and artificial intelligence / editors, H. Bunke, P.S.P. Wang, v. 7）
World Scientific, 1993
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Note
Includes bibliographical references
Description and Table of Contents
Description
Part of the Series in Machine Perception and Artificial Intelligence, this book deals with the principles and applications of pattern recognition systems using neural network technologies. It includes a chapter on a system for the recognition of partially occluded objects in cluttered scenes.
Table of Contents
- A connectionist approach to speech recognition, Y. Bengio
- signature verification with a Siamese TDNN, J. Bromley et al
- boosting performance in neural networks, H. Drucker et al
- an integrated architecture for recognition of totally unconstrained hand-written numerals, A. Gupta et al
- time warping network - a neural approach to hidden Markov model-based speech recognition, E. Levin et al
- computing optical flow with a recurrent neural network, H. Li and J. Wang
- integrated segmentation and recognition through exhaustive scans or learned Saccadic jumps, G. Martin et al
- experimental comparison of the effect of order in recurrent neural networks, C.B. Miller and C.L. Giles
- adaptive classification by neural net based prototype populations, K. Peleg and U. Ben Hanan
- a neural system for the recognition of partially occluded objects in cluttered scenes - a pilot study, L. Wiskott and C. von der Malsburg. (Part contents).
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