Zobrist, A.L.[Albert L.],
The organization of extracted features for pattern recognition,
PR(3), No. 1, April 1971, pp. 23-30.
WWW Version.
0309
A two layered pattern recognition program. The first layer scans
an input for features and produces a coded representation. The second layer
looks for combinations of code which signify relations between features
in the input.
BibRef
Haralick, R.M.[Robert M.],
Dinstein, I.,
An Iterative Clustering Procedure,
),
SMC(1), No. 3, July, 1971, pp. 275-289.
BibRef
7107
Biehl, L.L., and
Silva, L.F.,
A Multilevel Multispectral Data Set Analysis in the Visible and Infrared
Wavelength Regions,
PIEEE(63), No. 1, 1975, pp. 164-175.
BibRef
7500
Lukasová, A.[Alena],
Hierarchical agglomerative clustering procedure,
PR(11), No. 5-6, 1979, pp. 365-381.
WWW Version.
0309
BibRef
Smith, S.P.[Stephen P.],
Dubes, R.C.[Richard C.],
Stability of a hierarchical clustering,
PR(12), No. 3, 1980, pp. 177-187.
WWW Version.
0309
BibRef
Ozawa, K.[Kazumasa],
Classic: A hierarchical clustering algorithm based on asymmetric
similarities,
PR(16), No. 2, 1983, pp. 201-211.
WWW Version.
0309
BibRef
Ozawa, K.[Kazumasa],
A stratificational overlapping cluster scheme,
PR(18), No. 3-4, 1985, pp. 279-286.
WWW Version.
0309
BibRef
Perruchet, C.[Christophe],
Constrained agglomerative hierarchical classification,
PR(16), No. 2, 1983, pp. 213-217.
WWW Version.
0309
BibRef
Schuermann, J.[Juergen],
Doster, W.[Wolfgang],
A decision theoretic approach to hierarchical classifier design,
PR(17), No. 3, 1984, pp. 359-369.
WWW Version.
0309
BibRef
de Mŕntaras, R.L.[R. López],
Aguilar-Martín, J.,
Self-learning pattern classification using a sequential clustering
technique,
PR(18), No. 3-4, 1985, pp. 271-277.
WWW Version.
0309
BibRef
Jain, N.C.[Naresh C.],
Indrayan, A.[Abhaya],
Goel, L.R.[Lajpat R.],
Monte Carlo comparison of six hierarchical clustering methods on random
data,
PR(19), No. 1, 1986, pp. 95-99.
WWW Version.
0309
BibRef
Plastria, F.[Frank],
Two hierarchies associated with each clustering scheme,
PR(19), No. 2, 1986, pp. 193-196.
WWW Version.
0309
BibRef
Kurzynski, M.W.[Marek W.],
On the Identity of Optimal Strategies for Multistage Classifiers,
PRL(10), No. 1, 1989, pp. 39-46.
See also optimal strategy of a tree classifier, The.
See also On the multistage Bayes classifier.
BibRef
8900
Kurzynski, M.W.,
Puchala, E.,
Blinowska, A.,
A branch-and-bound algorithm for optimization of multiperspective
classifier,
ICPR94(B:235-239).
IEEE DOI Link
9410
BibRef
Kurzynski, M.W.,
Puchala, E.,
Algorithms of the multiperspective pattern recognition,
ICPR92(II:627-630).
IEEE DOI Link
9208
BibRef
Spivak, S.[Shalom],
A multisurface method for pattern classification,
PR(22), No. 5, 1989, pp. 587-591.
WWW Version.
0309
The desired classifier is built in two stages. In the first stage an
initial classifier is built. In the second stage the classifier is
modified to obtain the desired properties. Modification is performed
by use of the gradient descent procedure.
BibRef
Spivak, S.[Shalom],
Some properties of the multisurface method for pattern classification,
PR(24), No. 4, 1991, pp. 325-330.
WWW Version.
0401
BibRef
Li, X.,
Parallel algorithms for hierarchical clustering and cluster validity,
PAMI(12), No. 11, November 1990, pp. 1088-1092.
IEEE Abstract. IEEE Top Reference.
WWW Version.
0401
BibRef
Murtagh, F.,
Comments on 'Parallel algorithms for hierarchical clustering and
cluster validity',
PAMI(14), No. 10, October 1992, pp. 1056-1057.
IEEE Abstract. IEEE Top Reference.
WWW Version.
0401
BibRef
Zhang, Q.W.[Qi-Wen],
Boyle, R.D.[Roger D.],
A new clustering algorithm with multiple runs of iterative procedures,
PR(24), No. 9, 1991, pp. 835-848.
WWW Version.
0401
BibRef
Chan, K.P.,
Cheung, Y.S.,
Clustering of clusters,
PR(25), No. 2, February 1992, pp. 211-217.
WWW Version.
0401
BibRef
Liaw, J.N.[Jin-Nan],
Kashyap, R.L.,
A new sequential classifier using information criterion window,
PR(27), No. 10, October 1994, pp. 1423-1438.
WWW Version.
0401
BibRef
Zavaljevski, A.,
Dhawan, A.P.,
Kelch, D.J.,
Riddell, J.,
Adaptive Multilevel Classification and Detection in
Multispectral Images,
OptEng(35), No. 10, October 1996, pp. 2884-2893.
9611
BibRef
Bishop, C.M.,
Tipping, M.E.,
A Hierarchical Latent Variable Model For Data Visualization,
PAMI(20), No. 3, March 1998, pp. 281-293.
IEEE Abstract. IEEE Top Reference.
WWW Version.
9805
Visualize the data.
BibRef
El-Sonbaty, Y.[Yasser],
Ismail, M.A.,
On-line hierarchical clustering,
PRL(19), No. 14, December 1998, pp. 1285-1291.
BibRef
9812
Fisher, D.,
Iterative Optimization and Simplification of Hierarchical Clusterings,
JAIR(4), 1996, pp. 147-178.
HTML Version.
BibRef
9600
Labonté, G.,
On a Neural Network that Performs an Enhanced Nearest-Neighbour
Matching,
PAA(3), No. 3 2000, pp. 267-278.
0010
BibRef
Leung, Y.[Yee],
Zhang, J.S.[Jiang-She],
Xu, Z.B.[Zong-Ben],
Clustering by Scale-Space Filtering,
PAMI(22), No. 12, December 2000, pp. 1396-1410.
IEEE Abstract. IEEE Top Reference.
WWW Version.
0012
BibRef
Leung, Y.[Yee],
Ma, J.H.[Jiang-Hong],
Zhang, W.X.[Wen-Xiu],
A New Method for Mining Regression Classes in Large Data Sets,
PAMI(23), No. 1, January 2001, pp. 5-21.
IEEE Abstract. IEEE Top Reference.
WWW Version.
0101
Genetic algorithm. Regression class: subset of data subject to regression
model.
BibRef
Talavera, L.[Luis],
Béjar, J.[Javier],
Generality-Based Conceptual Clustering with Probabilistic Concepts,
PAMI(23), No. 2, February 2001, pp. 196-206.
IEEE Abstract. IEEE Top Reference.
WWW Version.
0102
BibRef
Fieguth, P.W.[Paul W.],
Multiply-rooted multiscale models for large-scale estimation,
IP(10), No. 11, November 2001, pp. 1676-1686.
IEEE DOI Link
0201
BibRef
Earlier:
Foveated Multiscale Models for Large-Scale Estimation,
ICIP99(II:871-874).
IEEE Abstract. IEEE Top Reference.
BibRef
Earlier:
Multipole-motivated reduced-state estimation,
ICIP98(I: 635-638).
IEEE DOI Link
9810
BibRef
Agnelli, D.[Davide],
Bollini, A.[Alessandro],
Lombardi, L.[Luca],
Image classification: an evolutionary approach,
PRL(23), No. 1-3, January 2002, pp. 303-309.
HTML Version.
0201
BibRef
Sun, Y.[Ying],
Zhu, Q.M.[Qiu-Ming],
Chen, Z.X.[Zheng-Xin],
An iterative initial-points refinement algorithm for categorical data
clustering,
PRL(23), No. 7, May 2002, pp. 875-884.
HTML Version.
0203
BibRef
Lam, W.[Wai],
Keung, C.K.[Chi-Kin],
Liu, D.Y.[Dan-Yu],
Discovering Useful Concept Prototypes for Classification Based on
Filtering and Abstraction,
PAMI(24), No. 8, August 2002, pp. 1075-1090.
IEEE Abstract. IEEE Top Reference.
0208
ICPL. Integrated Concept Prototype Learner.
Integrate instance filtering with instace abstraction.
BibRef
Fernández Prieto, D.,
An iterative approach to partially supervised classification problems,
JRS(23), No. 18, September 2002, pp. 3887-3892.
WWW Version.
0211
See also adaptive semiparametric and context-based approach to unsupervised change detection multitemporal remote-sensing images, An.
BibRef
Rodríguez, C.,
Soraluze, I.,
Muguerza, J.,
Martín, J.I.,
Álvarez, G.,
Hierarchical classifiers based on neighbourhood criteria with adaptive
computational cost,
PR(35), No. 12, December 2002, pp. 2761-2769.
WWW Version.
0209
BibRef
Vijaya, P.A.,
Murty, M.N.[M. Narasimha],
Subramanian, D.K.,
Leaders-Subleaders: An efficient hierarchical clustering algorithm for
large data sets,
PRL(25), No. 4, March 2004, pp. 505-513.
WWW Version.
0402
BibRef
Huber, R.[Reinhold],
Ramoser, H.[Herbert],
Mayer, K.[Konrad],
Penz, H.[Harald],
Rubik, M.[Michael],
Classification of coins using an eigenspace approach,
PRL(26), No. 1, 1 January 2005, pp. 61-75.
WWW Version.
Elsevier DOI Link
0501
Multistage classifier for large classes of coins.
BibRef
Hill, E.J.[E. June],
Alder, M.D.[Michael D.],
de Silva, C.J.S.[Christopher J.S.],
An improvement to the DR clustering algorithm,
PRL(26), No. 1, 1 January 2005, pp. 101-107.
WWW Version.
0501
Map data from a region to toroidal surface then run DR (Dog-Rabbit)
clustering.
BibRef
Lee, S.,
Crawford, M.M.,
Unsupervised Multistage Image Classification Using Hierarchical
Clustering With a Bayesian Similarity Measure,
IP(14), No. 3, March 2005, pp. 312-320.
IEEE DOI Link
0501
BibRef
Milgram, J.[Jonathan],
Sabourin, R.[Robert],
Cheriet, M.[Mohamed],
Combining Model-based and Discriminative Approaches in a Modular
Two-stage Classification System: Application to Isolated Handwritten
Digit Recognition,
ELCVIA(5), No. 2, 2005, pp. 1-15.
WWW Version.
0505
BibRef
Earlier:
Two-stage classification system combining model-based and
discriminative approaches,
ICPR04(I: 152-155).
IEEE DOI Link
0409
BibRef
Lee, J.W.T.[John W.T.],
Yeung, D.S.[Daniel S.],
Tsang, E.C.C.[Eric C.C.],
Hierarchical clustering based on ordinal consistency,
PR(38), No. 11, November 2005, pp. 1913-1925.
WWW Version.
0509
BibRef
Wang, D.,
Yeung, D.S.[Daniel S.],
Tsang, E.C.C.[Eric C.C.],
Structured One-Class Classification,
SMC-B(36), No. 6, December 2006, pp. 1283-1295.
IEEE DOI Link
0701
BibRef
Amador, J.J.[José J.],
Sequential clustering by statistical methodology,
PRL(26), No. 14, 15 October 2005, pp. 2152-2163.
WWW Version.
0510
BibRef
Dutta, M.,
Mahanta, A.K.[A. Kakoti],
Pujari, A.K.[Arun K.],
QROCK: A quick version of the ROCK algorithm for clustering of
categorical data,
PRL(26), No. 15, November 2005, pp. 2364-2373.
WWW Version.
0510
An agglomerative hierarchical clustering algorithm for
clustering categorical data.
BibRef
Zilong, G.[Guo],
Sun'an, W.[Wang],
Jian, Z.[Zhuang],
A novel immune evolutionary algorithm incorporating chaos optimization,
PRL(27), No. 1, 1 January 2006, pp. 2-8.
WWW Version.
0512
BibRef
Fränti, P.[Pasi],
Virmajoki, O.[Olli],
Iterative shrinking method for clustering problems,
PR(39), No. 5, May 2006, pp. 761-775.
WWW Version. Vector quantization; Codebook generation; Agglomeration; PNN
0604
BibRef
Earlier: A2, A1:
Divide-and-conquer algorithm for creating neighborhood graph for
clustering,
ICPR04(I: 264-267).
IEEE DOI Link
0409
BibRef
Virmajoki, O.,
Franti, P.,
Kaukoranta, T.,
Iterative shrinking method for generating clustering,
ICIP02(II: 685-688).
IEEE Abstract. IEEE Top Reference.
0210
BibRef
Nock, R.[Richard], and
Nielsen, F.[Frank],
On Weighting Clustering,
PAMI(28), No. 8, August 2006, pp. 1223-1235.
IEEE DOI Link
0606
BibRef
Earlier:
Improving clustering algorithms through constrained convex optimization,
ICPR04(IV: 557-560).
IEEE DOI Link
0409
Formalize unsupervised clustering ideas to take advantage of boosting ideas.
BibRef
Nock, R.[Richard],
Nielsen, F.[Frank],
Bregman Divergences and Surrogates for Learning,
PAMI(31), No. 11, November 2009, pp. 2048-2059.
IEEE DOI Link
0910
BibRef
Earlier: A2, A1:
Bregman sided and symmetrized centroids,
ICPR08(1-4).
IEEE DOI Link
0812
BibRef
Nock, R.[Richard],
Nielsen, F.[Frank],
On the efficient minimization of convex surrogates in supervised
learning,
ICPR08(1-4).
IEEE DOI Link
0812
BibRef
Nielsen, F.[Frank],
Nock, R.[Richard],
Clustering Multivariate Normal Distributions,
ETVC08(164-174).
Springer DOI Link
0811
BibRef
Nock, R.[Richard],
Nielsen, F.[Frank],
Intrinsic Geometries in Learning,
ETVC08(175-215).
Springer DOI Link
0811
BibRef
Nock, R.[Richard],
Vaillant, P.[Pascal],
Henry, C.[Claudia],
Nielsen, F.[Frank],
Soft memberships for spectral clustering, with application to permeable
language distinction,
PR(42), No. 1, January 2009, pp. 43-53.
WWW Version.
0809
Spectral clustering; Soft membership; Stochastic processes; Text classification
BibRef
Kushnir, D.[Dan],
Galun, M.[Meirav],
Brandt, A.[Achi],
Fast multiscale clustering and manifold identification,
PR(39), No. 10, October 2006, pp. 1876-1891.
WWW Version.
0606
Algebraic multigrid (AMG); Aggregation; Graph partitioning;
Similarity-based clustering; Manifold; Data analysis; Astrophysical models
BibRef
Martínez-Otzeta, J.M.,
Sierra, B.,
Lazkano, E.,
Astigarraga, A.,
Classifier hierarchy learning by means of genetic algorithms,
PRL(27), No. 16, December 2006, pp. 1998-2004.
WWW Version.
0611
Data mining; Classifier combination; Genetic algorithms
BibRef
Martínez-Otzeta, J.M.,
Sierra, B.,
Lazkano, E.,
Jauregi, E.,
Yurramendi, Y.,
Analyzing Classifier Hierarchy Multiclassifier Learning,
CIARP08(775-782).
Springer DOI Link
0809
BibRef
Cao, F.[Frédéric],
Delon, J.[Julie],
Desolneux, A.[Agnčs],
Musé, P.[Pablo],
Sur, F.[Frédéric],
A Unified Framework for Detecting Groups and Application to Shape
Recognition,
JMIV(27), No. 2, February 2007, pp. 91-119.
Springer DOI Link
0704
See also grouping principle and four applications, A. Evaluate validity of clusters, containment of clusters,
merging of clusters.
BibRef
Santos, J.M.[Jorge M.],
de Sa, J.M.[Joaquim Marques],
Alexandre, L.A.[Luis A.],
LEGClust: A Clustering Algorithm Based on Layered Entropic Subgraphs,
PAMI(30), No. 1, January 2008, pp. 62-75.
IEEE DOI Link
0711
Builds layers of subgraphs then applies clustering.
BibRef
Goldberger, J.[Jacob],
Tassa, T.[Tamir],
A hierarchical clustering algorithm based on the Hungarian method,
PRL(29), No. 11, 1 August 2008, pp. 1632-1638.
WWW Version.
0804
Grouping; Pairwise clustering; Hierarchical clustering; Graph algorithms
BibRef
Ning, H.Z.[Hua-Zhong],
Xu, W.[Wei],
Chi, Y.[Yun],
Gong, Y.H.[Yi-Hong],
Huang, T.S.[Thomas S.],
Incremental spectral clustering by efficiently updating the
eigen-system,
PR(43), No. 1, January 2010, pp. 113-127,.
Elsevier DOI Link
WWW Version.
0909
Incremental clustering; Spectral clustering; Incidence vector/matrix;
Graph; Web-blogs
BibRef
Dang, E.K.F.[Edward K. F.],
Luk, R.W.P.[Robert W. P.],
Lee, D.L.[Dik Lun],
Ho, K.S.[Kei-Shiu],
Chan, S.C.F.[Stephen C. F.],
Optimal Combination of Nested Clusters by a Greedy Approximation
Algorithm,
PAMI(31), No. 11, November 2009, pp. 2083-2087.
IEEE DOI Link
0910
BibRef
Fleck, D.[Daniel],
Duric, Z.[Zoran],
Affine Invariant-Based Classification of Inliers and Outliers for Image
Matching,
ICIAR09(268-277).
Springer DOI Link
0907
Evaluate tentative classifications using affine transformation model.
BibRef
Sledge, I.J.[Isaac J.],
Keller, J.M.[James M.],
Growing neural gas for temporal clustering,
ICPR08(1-4).
IEEE DOI Link
0812
Genetic Algorithm for clusters
BibRef
Kuncheva, L.I.[Ludmila I.],
Plumpton, C.O.[Catrin O.],
Adaptive Learning Rate for Online Linear Discriminant Classifiers,
SSPR08(510-519).
Springer DOI Link
0812
BibRef
Kuncheva, L.I.[Ludmila I.],
Zliobaite, I.[Indre],
Linear Discriminant Classifier (LDC) for Streaming Data with Concept
Drift,
SSPR08(4).
Springer DOI Link
0812
Trained using latest N observations.
BibRef
Elghazel, H.[Haytham],
Yoshida, T.[Tetsuya],
Deslandres, V.[Véronique],
Hacid, M.S.[Mohand-Said],
Dussauchoy, A.[Alain],
A New Greedy Algorithm for Improving b-Coloring Clustering,
GbRPR07(228-239).
Springer DOI Link
0706
BibRef
Aghagolzadeh, M.,
Soltanian-Zadeh, H.,
Araabi, B.,
Aghagolzadeh, A.,
A Hierarchical Clustering Based on Mutual Information Maximization,
ICIP07(I: 277-280).
IEEE DOI Link
0709
BibRef
Roth, V.[Volker],
Fischer, B.[Bernd],
The kernelHMM:
Learning Kernel Combinations in Structured Output Domains,
DAGM07(436-445).
Springer DOI Link
0709
BibRef
Sakai, T.[Tomoya],
Imiya, A.[Atsushi],
Validation of Watershed Regions by Scale-Space Statistics,
SSVM09(175-186).
Springer DOI Link
0906
BibRef
Sakai, T.[Tomoya],
Imiya, A.[Atsushi],
Statistically Valid Graph Representations of Scale-Space Geometry,
ICISP08(338-345).
Springer DOI Link
0807
BibRef
Sakai, T.[Tomoya],
Monte Carlo subspace method: An incremental approach to
high-dimensional data classification,
ICPR08(1-4).
IEEE DOI Link
0812
BibRef
Sakai, T.[Tomoya],
Komazaki, T.[Takuto],
Imiya, A.[Atsushi],
Scale-Space Clustering with Recursive Validation,
SSVM07(288-299).
Springer DOI Link
0705
BibRef
Karadag, O.O.[Ozge Oztimur],
Vural, F.T.Y.[Fatos T. Yarman],
HANOLISTIC: A Hierarchical Automatic Image Annotation System Using
Holistic Approach,
VCL-ViSU09(16-21).
IEEE DOI Link
0906
BibRef
Akbas, E.[Emre],
Vural, F.T.Y.[Fatos T. Yarman],
Automatic Image Annotation by Ensemble of Visual Descriptors,
SLAM07(1-8).
IEEE DOI Link
0706
Do not just add all the features, due to different types, redundancy.
Each feature learned at lowest level, combined at other levels.
BibRef
Yang, L.[Liu],
Jin, R.[Rong],
Pantofaru, C.[Caroline],
Sukthankar, R.[Rahul],
Discriminative Cluster Refinement: Improving Object Category
Recognition Given Limited Training Data,
CVPR07(1-8).
IEEE DOI Link
0706
BibRef
Pantofaru, C.,
Hebert, M.,
A framework for learning to recognize and segment object classes using
weakly supervised training data,
BMVC07(xx-yy).
PDF Version.
0709
BibRef
Monteleoni, C.[Claire],
Kaariainen, M.[Matti],
Practical Online Active Learning for Classification,
Learning07(1-8).
IEEE DOI Link
0706
BibRef
Gagrani, A.[Aakanksha],
Gupta, L.[Lalit],
Ravindran, B.,
Das, S.[Sukhendu],
Roychowdhury, P.[Pinaki],
Panchal, V.K.,
A Hierarchical Approach to Landform Classification of Satellite Images
Using a Fusion Strategy,
ICCVGIP06(140-151).
Springer DOI Link
0612
First into 3 major landforms, then classify within each of these.
BibRef
Sternby, J.[Jakob],
Class Dependent Cluster Refinement,
ICPR06(II: 833-836).
WWW Version.
0609
BibRef
Lam, B.S.Y.[Benson S. Y.],
Yan, H.[Hong],
Improved Clustering Algorithm Based on Calculus of Variation,
ICPR06(I: 900-903).
WWW Version.
0609
BibRef
Prehn, H.[Herward],
Sommer, G.[Gerald],
An Adaptive Classification Algorithm Using Robust Incremental
Clustering,
ICPR06(I: 896-899).
WWW Version.
0609
BibRef
Azran, A.[Arik],
Ghahramani, Z.[Zoubin],
Spectral Methods for Automatic Multiscale Data Clustering,
CVPR06(I: 190-197).
IEEE DOI Link
0606
BibRef
Zhang, K.[Kai],
Tang, M.[Ming],
Kwok, J.T.[James T.],
Applying Neighborhood Consistency for Fast Clustering and Kernel
Density Estimation,
CVPR05(II: 1001-1007).
IEEE DOI Link
0507
BibRef
Carrivick, L.[Luke],
Prabhu, S.[Sanjay],
Goddard, P.[Paul],
Rossiter, J.[Jonathan],
Unsupervised Learning in Radiology Using Novel Latent Variable Models,
CVPR05(II: 854-859).
IEEE DOI Link
0507
BibRef
Bouvrie, J.V.[Jake V.],
Multiple Resolution Image Classification,
MIT AIMAIM-2002-022, December 2002.
WWW Version. In this paper we evaluate a
selection of popular techniques in an effort to find a feature set/ classifier combination which generalizes well to full
resolution image data.
0306
BibRef
Shi, S.[Shuming],
Yang, G.[Guangwen],
Wang, D.X.[Ding-Xing],
Zheng, W.M.[Wei-Min],
Potential-based hierarchical clustering,
ICPR02(IV: 272-275).
IEEE DOI Link
0211
BibRef
Rendon, E.,
Barandela, R.,
Fast hierarchical clustering based on compressed data,
ICPR02(II: 216-219).
IEEE DOI Link
0211
BibRef
Zöller, T.,
Buhmann, J.M.,
Active Learning for Hierarchical Pairwise Data Clustering,
ICPR00(Vol II: 186-189).
IEEE DOI Link
HTML Version.
0009
BibRef
Chardin, A.,
Perez, P.,
Unsupervised Image Classification with a Hierarchical EM Algorithm,
ICCV99(969-974).
IEEE DOI Link
BibRef
9900
Earlier:
Semi-iterative inference with hierarchical models,
ICIP98(I: 630-634).
IEEE DOI Link
9810
BibRef
Li, J.[Jia],
Gray, R.M.,
Context based multiscale classification of images,
ICIP98(III: 566-570).
IEEE DOI Link
9810
BibRef
Schikuta, E.,
Grid-Clustering:
An Efficient Hierarchical Clustering Method for Very Large Data Sets,
ICPR96(II: 101-105).
IEEE DOI Link
9608
(Univ. of Vienna, A)
BibRef
Bajcsy, P.,
Ahuja, N.,
Uniformity and Homogeneity Based Hierarchical Clustering,
ICPR96(II: 96-100).
IEEE DOI Link
9608
(Univ. of Illinois, Urbana, USA)
BibRef
Roberts, S.J.,
Scale-Space Unsupervised Cluster Analysis,
ICPR96(II: 106-110).
IEEE DOI Link
9608
(Univ. of London, UK)
BibRef
Jin, J.S.,
Hierarchical pattern matching using a high entropy signature,
ICPR94(B:436-438).
IEEE DOI Link
9410
BibRef
Prabhu, S.M.,
Garg, D.P.,
Spano, Sr., M.R.,
A hierarchical labeled object classification system,
ICPR94(B:479-481).
IEEE DOI Link
9410
BibRef
Jiang, H.T.[Hong-Tao],
Bolviken, E.,
A general parameter updating approach to image classification,
ICPR94(A:720-722).
IEEE DOI Link
9410
BibRef
Tseng, C.T.,
Moret, B.M.E.,
The design of a nonparametric hierarchical classifier,
ICPR90(I: 428-432).
IEEE DOI Link
9006
BibRef
Li, X.,
Hierarchical clustering on SIMD machines with alignment network,
CVPR89(660-665).
IEEE Abstract. IEEE Top Reference.
0403
BibRef
Chapter on Pattern Recognition, Clustering, Statistics, Grammars, Learning, Neural Nets, Genetic Algorithms continues in
Distance Measures, Criteria for Clustering .