Lakany, H.M.,
Schukat-Talamazzini, E.G.,
Niemann, H., and
Ghonaimy, M.A.R.,
Object recognition from 2D images using Kohonen
self-organized feature maps,
PRIA(7), 1997, pp. 301-308.
BibRef
9700
Hogg, T.[Trevor],
Talhami, H.[Habib],
Rees, D.[David],
Learning in a self-organising pattern formation system,
PRL(20), No. 1, January 1999, pp. 1-5.
BibRef
9901
Suganthan, P.N.,
Pattern classification using multiple hierarchical overlapped
self-organising maps,
PR(34), No. 11, November 2001, pp. 2173-2179.
Elsevier DOI
0108
BibRef
Laha, A.,
Pal, N.R.,
Some novel classifiers designed using prototypes extracted by a new
scheme based on self-organizing feature map,
SMC-B(31), No. 6, December 2001, pp. 881-890.
IEEE Top Reference.
0201
See also Design of Vector Quantizer for Image Compression Using Self-Organizing Feature Map and Surface Fitting.
BibRef
Wu, S.[Sitao],
Chow, T.W.S.[Tommy W. S.],
Clustering of the self-organizing map using a clustering validity index
based on inter-cluster and intra-cluster density,
PR(37), No. 2, February 2004, pp. 175-188.
Elsevier DOI
0311
Self organizing map.
BibRef
Simon, G.,
Lendasse, A.,
Cottrell, M.,
Fort, J.C.,
Verleysen, M.,
Time series forecasting:
Obtaining long term trends with self-organizing maps,
PRL(26), No. 12, September 2005, pp. 1795-1808.
Elsevier DOI
0508
BibRef
Hagenbuchner, M.[Markus],
Tsoi, A.C.[Ah Chung],
A supervised training algorithm for self-organizing maps for structures,
PRL(26), No. 12, September 2005, pp. 1874-1884.
Elsevier DOI
0508
BibRef
Lee, S.,
Lathrop, R.G.,
Subpixel Analysis of Landsat (rm ETM) Using Self-Organizing Map (SOM)
Neural Networks for Urban Land Cover Characterization,
GeoRS(44), No. 6, June 2006, pp. 1642-1654.
IEEE DOI
0606
BibRef
Liu, L.F.[Li-Fan],
Wang, B.[Bin],
Zhang, L.M.[Li-Ming],
Decomposition of Mixed Pixels Based on Bayesian Self-Organizing Map and
Gaussian Mixture Model,
PRL(30), No. 9, 1 July 2009, pp. 820-826.
Elsevier DOI
0905
Decomposition of mixed pixels; Bayesian self-organization map (BSOM);
Gaussian mixture model (GMM); Multispectral/hyperspectral data
BibRef
Liu, L.[Lifan],
Wang, B.[Bin],
Zhang, L.M.[Li-Ming],
An approach based on self-organizing map and fuzzy membership for
decomposition of mixed pixels in hyperspectral imagery,
PRL(31), No. 11, 1 August 2010, pp. 1388-1395.
Elsevier DOI
1008
Mixed pixel; Spectral unmixing; Endmember; Abundance; Self-organizing
map neural network; Fuzzy membership
BibRef
Su, M.C.[Mu-Chun],
Su, S.Y.[Shi-Yong],
Zhao, Y.X.[Yu-Xiang],
A swarm-inspired projection algorithm,
PR(42), No. 11, November 2009, pp. 2764-2786.
Elsevier DOI
0907
Cluster analysis; Projection; Neural networks; Self-organizing feature
map; Swarm intelligence
BibRef
Sarlin, P.[Peter],
Decomposing the global financial crisis: A Self-Organizing Time Map,
PRL(34), No. 14, 2013, pp. 1701-1709.
Elsevier DOI
1308
Self-Organizing Time Map
BibRef
Astudillo, C.A.[César A.],
Oommen, B.J.[B. John],
Self-organizing maps whose topologies can be learned with adaptive
binary search trees using conditional rotations,
PR(47), No. 1, 2014, pp. 96-113.
Elsevier DOI
1310
Adaptive data structures
BibRef
Cabanes, G.[Guénaël],
Bennani, Y.[Younès],
Destenay, R.[Renaud],
Hardy, A.[André],
A new topological clustering algorithm for interval data,
PR(46), No. 11, November 2013, pp. 3030-3039.
Elsevier DOI
1306
Interval data; Clustering; Self-organizing map
BibRef
Clark, S.[Stephanie],
Sisson, S.A.[Scott. A.],
Sharma, A.[Ashish],
A dimension range representation (DRR) measure for self-organizing
maps,
PR(53), No. 1, 2016, pp. 276-286.
Elsevier DOI
1602
Self-organizing maps
BibRef
Zheng, H.C.[Hui-Cheng],
Invariant Feature Set Generation with the Linear Manifold
Self-organizing Map,
ACCV10(IV: 677-689).
Springer DOI
1011
manifold representation using neural networks to model human brain.
BibRef
Fornells, A.,
Golobardes, E.,
Martorell, J.M.,
Garrell, J.M.,
Bernadó, E.,
Maciá, N.,
Measuring the Applicability of Self-organization Maps in a Case-Based
Reasoning System,
IbPRIA07(II: 532-539).
Springer DOI
0706
BibRef
Guan, L.[Ling],
Self-Organizing Trees and Forests:
A Powerful Tool in Pattern Clustering and Recognition,
ICIAR06(I: 1-14).
Springer DOI
0610
BibRef
Kyan, M.[Matthew],
Guan, L.[Ling],
Local Variance Driven Self-Organization for Unsupervised Clustering,
ICPR06(III: 421-424).
IEEE DOI
0609
BibRef
Smolander, S.[Seppo], and
Lampinen, J.[Jouko],
Determining the Optimal Structure for Multilayer Self-Organizing Map
with Genetic Algorithm,
SCIA97(xx-yy)
HTML Version.
9705
BibRef
Mulier, F.,
Cherkassky, V.S.[Vladimir S.],
Learning rate schedules for self-organizing maps,
ICPR94(B:224-228).
IEEE DOI
9410
BibRef
Chapter on Pattern Recognition, Clustering, Statistics, Grammars, Learning, Neural Nets, Genetic Algorithms continues in
Context and Structure for Classification .