Applications of CNN processing by template decomposition

Bahram Mirzai; Drahoslav Lim; George S. Moschytz

Applications of CNN processing by template decomposition

Bahram Mirzai, Drahoslav Lim, George S. Moschytz

Signal and Information Processing

Research output: Contribution to conference › Paper › peer-review

1 Scopus citations

Abstract

High connectivity CNN templates are inherently less robust than templates of lower connectivity. However, some types of detection tasks requiring a high degree of connectivity can be decomposed and realized by an algorithmic approach, instead of a single CNN template. The processing comprises several robust template types and logical operations. The basic template type proposed for the decomposition is at an intermediate point between high-connectivity CNN template processing and processing using digital logic exclusively.

Original language	English
Pages	379-384
Number of pages	6
State	Published - 1998
Externally published	Yes
Event	Proceedings of the 1998 5th IEEE International Workshop on Cellular Neural Networks and Their Applications, CNNA - London, UK Duration: 14 Apr 1998 → 17 Apr 1998

Conference

Conference	Proceedings of the 1998 5th IEEE International Workshop on Cellular Neural Networks and Their Applications, CNNA
City	London, UK
Period	14/04/98 → 17/04/98

Cite this

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title = "Applications of CNN processing by template decomposition",

abstract = "High connectivity CNN templates are inherently less robust than templates of lower connectivity. However, some types of detection tasks requiring a high degree of connectivity can be decomposed and realized by an algorithmic approach, instead of a single CNN template. The processing comprises several robust template types and logical operations. The basic template type proposed for the decomposition is at an intermediate point between high-connectivity CNN template processing and processing using digital logic exclusively.",

author = "Bahram Mirzai and Drahoslav Lim and Moschytz, {George S.}",

year = "1998",

language = "אנגלית",

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note = "Proceedings of the 1998 5th IEEE International Workshop on Cellular Neural Networks and Their Applications, CNNA ; Conference date: 14-04-1998 Through 17-04-1998",

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AU - Mirzai, Bahram

AU - Lim, Drahoslav

AU - Moschytz, George S.

PY - 1998

Y1 - 1998

N2 - High connectivity CNN templates are inherently less robust than templates of lower connectivity. However, some types of detection tasks requiring a high degree of connectivity can be decomposed and realized by an algorithmic approach, instead of a single CNN template. The processing comprises several robust template types and logical operations. The basic template type proposed for the decomposition is at an intermediate point between high-connectivity CNN template processing and processing using digital logic exclusively.

AB - High connectivity CNN templates are inherently less robust than templates of lower connectivity. However, some types of detection tasks requiring a high degree of connectivity can be decomposed and realized by an algorithmic approach, instead of a single CNN template. The processing comprises several robust template types and logical operations. The basic template type proposed for the decomposition is at an intermediate point between high-connectivity CNN template processing and processing using digital logic exclusively.

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SP - 379

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T2 - Proceedings of the 1998 5th IEEE International Workshop on Cellular Neural Networks and Their Applications, CNNA

Y2 - 14 April 1998 through 17 April 1998

ER -

Applications of CNN processing by template decomposition

Abstract

Conference

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