A Concurrent SOM-Based Chan-Vese Model for Image Segmentation

Mohammed M. Abdelsamea; Giorgio Gnecco; Mohamed Medhat Gaber

doi:10.1007/978-3-319-07695-9_19

A Concurrent SOM-Based Chan-Vese Model for Image Segmentation

Mohammed M. Abdelsamea, Giorgio Gnecco, Mohamed Medhat Gaber

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

13 Citations (SciVal)

Original language	English
Title of host publication	Advances in Self-Organizing Maps and Learning Vector Quantization - Proceedings of the 10th International Workshop, WSOM 2014
Publisher	Springer Verlag
Pages	199-208
Number of pages	10
ISBN (Print)	9783319076942
DOIs	https://doi.org/10.1007/978-3-319-07695-9_19
Publication status	Published (VoR) - 2014

Publication series

Name	Advances in Intelligent Systems and Computing
Volume	295
ISSN (Print)	2194-5357

Keywords

Chan-Vese model
Concurrent Self Organizing Maps
Image segmentation
global active contours
neural networks

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10.1007/978-3-319-07695-9_19

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Abdelsamea, M. M., Gnecco, G., & Gaber, M. M. (2014). A Concurrent SOM-Based Chan-Vese Model for Image Segmentation. In Advances in Self-Organizing Maps and Learning Vector Quantization - Proceedings of the 10th International Workshop, WSOM 2014 (pp. 199-208). (Advances in Intelligent Systems and Computing; Vol. 295). Springer Verlag. https://doi.org/10.1007/978-3-319-07695-9_19

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title = "A Concurrent SOM-Based Chan-Vese Model for Image Segmentation",

keywords = "Chan-Vese model, Concurrent Self Organizing Maps, Image segmentation, global active contours, neural networks",

author = "Abdelsamea, {Mohammed M.} and Giorgio Gnecco and Gaber, {Mohamed Medhat}",

year = "2014",

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language = "English",

isbn = "9783319076942",

series = "Advances in Intelligent Systems and Computing",

publisher = "Springer Verlag",

pages = "199--208",

booktitle = "Advances in Self-Organizing Maps and Learning Vector Quantization - Proceedings of the 10th International Workshop, WSOM 2014",

}

A Concurrent SOM-Based Chan-Vese Model for Image Segmentation. / Abdelsamea, Mohammed M.; Gnecco, Giorgio; Gaber, Mohamed Medhat.
Advances in Self-Organizing Maps and Learning Vector Quantization - Proceedings of the 10th International Workshop, WSOM 2014. Springer Verlag, 2014. p. 199-208 (Advances in Intelligent Systems and Computing; Vol. 295).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - A Concurrent SOM-Based Chan-Vese Model for Image Segmentation

AU - Abdelsamea, Mohammed M.

AU - Gnecco, Giorgio

AU - Gaber, Mohamed Medhat

PY - 2014

Y1 - 2014

KW - Chan-Vese model

KW - Concurrent Self Organizing Maps

KW - Image segmentation

KW - global active contours

KW - neural networks

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U2 - 10.1007/978-3-319-07695-9_19

DO - 10.1007/978-3-319-07695-9_19

M3 - Conference contribution

AN - SCOPUS:84903512615

SN - 9783319076942

T3 - Advances in Intelligent Systems and Computing

SP - 199

EP - 208

BT - Advances in Self-Organizing Maps and Learning Vector Quantization - Proceedings of the 10th International Workshop, WSOM 2014

PB - Springer Verlag

ER -

A Concurrent SOM-Based Chan-Vese Model for Image Segmentation

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