Cascaded and Parallel Neural Network Architectures for Machine Vision — A Case Study

Littmann E, Meyering A, Ritter H (1992)
In: Mustererkennung 1992. 14. DAGM-Symposium, Dresden, 14.–16. September 1992. Fuchs S (Ed); Informatik aktuell, . Berlin: DAGM: 81-87.

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Author
; ;
Editor
Fuchs, S.
Abstract
Neural networks have emerged as an efficient method to complement more traditional approaches, in particular in situations where a design of algorithms from first principles becomes too costly or fails due to insufficient information about e.g. the statistics of a problem. However, as the problems to which neural networks are applied become more demanding, such as in machine vision, the choice of an adequate network architecture becomes more and more a crucial issue. This is particularly true for larger applications, where the actions of several neural networks need to be coherently integrated into a larger system. Unfortunately, systematic investigations of this issue are just beginning to appear in the literature (for an interesting approach, see e.g. [2, 12]) and results are still rather sparse.
Publishing Year
Conference
14. DAGM-Symposium
Location
Dresden
Conference Date
1992-09-14 – 1992-09-16
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Cite this

Littmann E, Meyering A, Ritter H. Cascaded and Parallel Neural Network Architectures for Machine Vision — A Case Study. In: Fuchs S, ed. Mustererkennung 1992. 14. DAGM-Symposium, Dresden, 14.–16. September 1992. Informatik aktuell. Berlin: DAGM; 1992: 81-87.
Littmann, E., Meyering, A., & Ritter, H. (1992). Cascaded and Parallel Neural Network Architectures for Machine Vision — A Case Study. In S. Fuchs (Ed.), Informatik aktuell. Mustererkennung 1992. 14. DAGM-Symposium, Dresden, 14.–16. September 1992 (pp. 81-87). Berlin: DAGM.
Littmann, E., Meyering, A., and Ritter, H. (1992). “Cascaded and Parallel Neural Network Architectures for Machine Vision — A Case Study” in Mustererkennung 1992. 14. DAGM-Symposium, Dresden, 14.–16. September 1992, ed. S. Fuchs Informatik aktuell (Berlin: DAGM), 81-87.
Littmann, E., Meyering, A., & Ritter, H., 1992. Cascaded and Parallel Neural Network Architectures for Machine Vision — A Case Study. In S. Fuchs, ed. Mustererkennung 1992. 14. DAGM-Symposium, Dresden, 14.–16. September 1992. Informatik aktuell. Berlin: DAGM, pp. 81-87.
E. Littmann, A. Meyering, and H. Ritter, “Cascaded and Parallel Neural Network Architectures for Machine Vision — A Case Study”, Mustererkennung 1992. 14. DAGM-Symposium, Dresden, 14.–16. September 1992, S. Fuchs, ed., Informatik aktuell, Berlin: DAGM, 1992, pp.81-87.
Littmann, E., Meyering, A., Ritter, H.: Cascaded and Parallel Neural Network Architectures for Machine Vision — A Case Study. In: Fuchs, S. (ed.) Mustererkennung 1992. 14. DAGM-Symposium, Dresden, 14.–16. September 1992. Informatik aktuell. p. 81-87. DAGM, Berlin (1992).
Littmann, Enno, Meyering, Andrea, and Ritter, Helge. “Cascaded and Parallel Neural Network Architectures for Machine Vision — A Case Study”. Mustererkennung 1992. 14. DAGM-Symposium, Dresden, 14.–16. September 1992. Ed. S. Fuchs. Berlin: DAGM, 1992. Informatik aktuell. 81-87.
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