Digital Signal Processing Reference
In-Depth Information
70.
C. Kotropoulos and I. Pitas, A variant of learning vector quantizer based on split-
merge statistical tests, in Lecture Notes in Computer Science: Computer Analysis
of Images and Patterns, D. Chetverikov and W.G. Kropatsch, Eds., New York:
Springer-Verlag, 1993, 822-829.
71.
C. Kotropoulos and I. Pitas, Split-merge learning vector quantizer algorithm, in
Proc. of the European Conference on Circuit Theory and Design (ECCTD '93), Davos,
Switzerland, 1993, 465-468.
72.
C. Kotropoulos, E. Auge, and I. Pitas, Two-layer learning vector quantizer for
color image quantization, in Signal Processing VI: Theories and Applications, Ams-
terdam: Elsevier, 1992, 1177-1180.
73.
P.K. Simpson, Artificial Neural Systems , Oxford: Pergamon Press, 1990.
74.
J. Laaksonen, M. Koskela, and E. Oja, PicSOM-Self-organizing image retrieval
with MPEG-7 content descriptors, IEEE Trans. Neural Networks, 13(4), 841-853,
July 2002. Working demonstration available at http://www.cis.hut.fi/picsom/.
75.
J. Besag, On the statistical analysis of dirty pictures, J. R. Stat. Soc. B, 48(3), 259-
302, 1986.
76.
T. Pappas, An adaptive clustering algorithm for image segmentation, IEEE Trans.
Signal Process. , 40(4), 901-914, April 1992.
77.
E. Pranckeviciene, C. Kotropoulos, and I. Pitas, Still image segmentation by us-
ing iterative conditional modes and split-merge self-organizing maps, in prepa-
ration.
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