Texture classification, texture segmentation and text segmentation with discrete-time cellular neural networks

Andreas Kellner; Holger Magnussen; Josef A. Nossek

Texture classification, texture segmentation and text segmentation with discrete-time cellular neural networks

Andreas Kellner, Holger Magnussen, Josef A. Nossek

Chair of Circuit Theory and Signal Processing (2008 — 2021)

Technical University of Munich

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

9 Scopus citations

Abstract

Global Learning Algorithms presented in a companion paper are applied to practical classification and segmentation problems: Texture Classification and Texture Segmentation of artificial and natural textures, and Text Segmentation as a sub-problem of Page Layout Analysis. In all cases, DTCNN systems can solve the problem very well in spite of its only local interconnection structure.

Original language	English
Pages	243-248
Number of pages	6
State	Published - 1994
Event	Proceedings of the 3rd IEEE International Workshop on Cellular Neural Networks and their Applications (CNNA-94) - Rome, Italy Duration: 18 Dec 1994 → 21 Dec 1994

Conference

Conference	Proceedings of the 3rd IEEE International Workshop on Cellular Neural Networks and their Applications (CNNA-94)
City	Rome, Italy
Period	18/12/94 → 21/12/94

Cite this

@conference{b4812acaad804b7eb536421bfc553365,

title = "Texture classification, texture segmentation and text segmentation with discrete-time cellular neural networks",

abstract = "Global Learning Algorithms presented in a companion paper are applied to practical classification and segmentation problems: Texture Classification and Texture Segmentation of artificial and natural textures, and Text Segmentation as a sub-problem of Page Layout Analysis. In all cases, DTCNN systems can solve the problem very well in spite of its only local interconnection structure.",

author = "Andreas Kellner and Holger Magnussen and Nossek, {Josef A.}",

year = "1994",

language = "English",

pages = "243--248",

note = "Proceedings of the 3rd IEEE International Workshop on Cellular Neural Networks and their Applications (CNNA-94) ; Conference date: 18-12-1994 Through 21-12-1994",

}

Texture classification, texture segmentation and text segmentation with discrete-time cellular neural networks. / Kellner, Andreas; Magnussen, Holger; Nossek, Josef A.
1994. 243-248 Paper presented at Proceedings of the 3rd IEEE International Workshop on Cellular Neural Networks and their Applications (CNNA-94), Rome, Italy.

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

TY - CONF

T1 - Texture classification, texture segmentation and text segmentation with discrete-time cellular neural networks

AU - Kellner, Andreas

AU - Magnussen, Holger

AU - Nossek, Josef A.

PY - 1994

Y1 - 1994

N2 - Global Learning Algorithms presented in a companion paper are applied to practical classification and segmentation problems: Texture Classification and Texture Segmentation of artificial and natural textures, and Text Segmentation as a sub-problem of Page Layout Analysis. In all cases, DTCNN systems can solve the problem very well in spite of its only local interconnection structure.

AB - Global Learning Algorithms presented in a companion paper are applied to practical classification and segmentation problems: Texture Classification and Texture Segmentation of artificial and natural textures, and Text Segmentation as a sub-problem of Page Layout Analysis. In all cases, DTCNN systems can solve the problem very well in spite of its only local interconnection structure.

UR - http://www.scopus.com/inward/record.url?scp=0028748339&partnerID=8YFLogxK

M3 - Paper

AN - SCOPUS:0028748339

SP - 243

EP - 248

T2 - Proceedings of the 3rd IEEE International Workshop on Cellular Neural Networks and their Applications (CNNA-94)

Y2 - 18 December 1994 through 21 December 1994

ER -

Texture classification, texture segmentation and text segmentation with discrete-time cellular neural networks

Abstract

Conference

Other files and links

Fingerprint

Cite this