Neural Networks In Vision And Pattern Recognition
World Scientific Publishing Co Pte Ltd (Verlag)
978-981-02-1014-4 (ISBN)
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The neural network paradigm with its various advantages might be the next promising bridge between artificial intelligence and pattern recognition that will help with the conceptualization of new computational artifacts. This volume contains ten papers which represent some of the work being done in the field, such as in computational neuroscience, pattern recognition, computational vision, and applications.
Lightness constancy from luminance contrast, J. Skrzypek and D. Gungner; bringing the grandmother back into the picture - a memory-based view of object recognition, S. Edelman and T. Poggio; internal organization of classifier networks trained by backpropagation, D.F. Michaels; system identification with artificial neural networks, E.R. Tisdale and W.J. Karplus; mixed finite element based neural networks in visual reconstruction, D. Suter; the random "Neural" network model for texture generation, V. Atalay, et al; neural networks for collective translational invariant object recognition, L.W. Chan; image recognition and reconstruction using associative magnetic processing, J.M. Goodwin, et al; incorporating uncertainty in neural networks, B.R. Kammerer; neural networks for the recognition of engraved musical scores, P. Martin and C. Bellissant.
| Erscheint lt. Verlag | 1.7.1992 |
|---|---|
| Reihe/Serie | Series In Machine Perception And Artificial Intelligence ; 3 |
| Verlagsort | Singapore |
| Sprache | englisch |
| Themenwelt | Informatik ► Theorie / Studium ► Künstliche Intelligenz / Robotik |
| ISBN-10 | 981-02-1014-0 / 9810210140 |
| ISBN-13 | 978-981-02-1014-4 / 9789810210144 |
| Zustand | Neuware |
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