7.2.1.3.1 MDL, Minimum Description Length for Shape Measure

Chapter Contents (Back)
Shape Measure. MDL. Minimum Description Length.

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Rissanen, J.J.[Jorma J.],
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Rissanen, J.J.[Jorma J.],
The Minimum Description Length (MDL) Principle and its Applications to Pattern Classification,
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Leonardis, A.[Ales], Bischof, H.[Horst],
An Efficient MDL-Based Construction of RBF Networks,
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Bischof, H.[Horst], Leonardis, A.[Ales],
MDL-Based Design of Vector Quantizers,
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Leonardis, A., Bischof, H.,
Complexity Optimization Of Adaptive Rbf Networks,
ICPR96(IV: 654-658).
IEEE DOI 9608
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Bischof, H.[Horst], Leonardis, A.[Ales], Selb, A.[Alexander],
MDL Principle for Robust Vector Quantisation,
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Selb, A., Bischof, H., Leonardis, A.,
Fuzzy C-means in an MDL-framework,
ICPR00(Vol II: 740-743).
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Canning, J.,
A Minimum Description Length Model for Recognizing Objects with Variable Appearances (The Vapor Model),
PAMI(16), No. 10, October 1994, pp. 1032-1036.
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Davies, R.H., Twining, C.J., Cootes, T.F., Waterton, J.C., Taylor, C.J.,
A minimum description length approach to statistical shape modeling,
MedImg(21), No. 5, May 2002, pp. 525-537.
IEEE Top Reference. 0206
MDL BibRef


Haralick, R.M.[Robert M.], Diky, A.[Art], Su, X.[Xing], Kiang, N.Y.[Nancy Y.],
Inexact MDL for linear manifold clusters,
ICPR16(1345-1351)
IEEE DOI 1705
Clustering algorithms, Data models, Encoding, Entropy, Histograms, Manifolds, Prototypes BibRef

Ramírez, I.[Ignacio], Tepper, M.[Mariano],
Bi-clustering via MDL-Based Matrix Factorization,
CIARP13(I:230-237).
Springer DOI 1311
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Lai, Y.N.[Yu Ning], Yuen, S.Y.[Shiu Yin],
Successive-least-squares error algorithm on minimum description length neural networks for time series prediction,
ICPR04(IV: 609-612).
IEEE DOI 0409
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Ericsson, A., Astrom, K.,
Minimizing the description length using steepest descent,
BMVC03(xx-yy).
HTML Version. 0409
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Thodberg, H.H., Olafsdottir, H.,
Adding Curvature to Minimum Description Length Shape Models,
BMVC03(xx-yy).
HTML Version. 0409
MDL BibRef

Thodberg, H.H.,
Minimum Description Length Shape and Appearance Models,
MedicalImaging03(51-62). BibRef 0300

Kudo, M., Shimbo, M.,
Selection of Classifiers Based on the MDL Principle Using the VC Dimension,
ICPR96(II: 886-890).
IEEE DOI 9608
(Hokkaido Univ., J) BibRef

Murthy, C.A., Chatterjee, N., Shankar, B.U.[B. Uma], Majumder, D.D.[D. Dutta],
IRS Image Segmentation: Minimum Distance Classifier Approach,
ICPR92(I:781-784).
IEEE DOI BibRef 9200

Chapter on 2-D Feature Analysis, Extraction and Representations, Shape, Skeletons, Texture continues in
Convex Hull Algorithms and Convexity Analysis .


Last update:Dec 7, 2017 at 17:23:10