SCOPUS 정보 검색 플랫폼

WSOM 2005 - 5th Workshop on Self-Organizing Maps

Volumn , Issue , 2005, Pages 331-338

Gradient visualization of grouped component planes on the SOM lattice

(3) Pölzlbauer, Georg a Dittenbach, Michael b Rauber, Andreas a

a VIENNA UNIVERSITY OF TECHNOLOGY (Austria)

b E Commerce Competence Center (Austria)

Author keywords

Dual gradient fields; Groups of component planes; Visualization

Indexed keywords

CLUSTER CENTERS; DOMAIN EXPERTS; FEATURE DIMENSIONS; GRADIENT FIELDS; GROUPS OF COMPONENT PLANES; MULTIPLE DEPENDENCIES; MUTUAL DEPENDENCIES; VECTOR FIELDS;

CONFORMAL MAPPING; FLOW VISUALIZATION; INDUSTRIAL APPLICATIONS; PETROLEUM ENGINEERING;

VISUALIZATION;

EID: 84890303896 PISSN: None EISSN: None Source Type: Conference Proceeding
DOI: None Document Type: Conference Paper

Times cited : (4)

References (8)

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- Denny¹ Squire, D.²

2
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- Himberg, J.¹

3
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- Bibliography of self-organizing map (SOM) papers: 1998-2001 addendum
- M. Oja, S. Kaski, and T. Kohonen. Bibliography of self-organizing map (SOM) papers: 1998-2001 addendum. Neural Computing Surveys, 3: 1-156, 2001.
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- Oja, M.¹ Kaski, S.² Kohonen, T.³

4
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- Advanced visualization techniques for self-organizing maps with graph-based methods
- G. Pölzlbauer, A. Rauber, and M. Dittenbach. Advanced visualization techniques for self-organizing maps with graph-based methods. In Intl. Symp. on Neural Networks (ISSN'05), 2005.
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- Pölzlbauer, G.¹ Rauber, A.² Dittenbach, M.³

5
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- A visualization technique for self-organizing maps with vector fields to obtain the cluster structure at desired levels of detail
- G. Pölzlbauer, A. Rauber, and M. Dittenbach. A visualization technique for self-organizing maps with vector fields to obtain the cluster structure at desired levels of detail. In International Joint Conference on Neural Networks (IJCNN'05), 2005.
- (2005) International Joint Conference on Neural Networks (IJCNN'05)
- Pölzlbauer, G.¹ Rauber, A.² Dittenbach, M.³

6
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- Som-based data visualization methods
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- Vesanto, J.¹

7
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- Hunting for correlations in data using the self-organizing map
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8
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* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.