14.2.6 Iterative, Hierarchical Clustering Techniques

Chapter Contents (Back)
Hierarchical Classification. Iterative Classification. Clustering, Iterative. Clustering, Hierarchical. 9905

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Amador, J.J.[José J.],
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Dutta, M., Mahanta, A.K.[A. Kakoti], Pujari, A.K.[Arun K.],
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Nock, R.[Richard], and Nielsen, F.[Frank],
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IEEE DOI 0409
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Nock, R.[Richard], Nielsen, F.[Frank],
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Nielsen, F.[Frank], Nock, R.[Richard],
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IEEE DOI 1407
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Springer DOI 0811
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Nielsen, F.[Frank], Nock, R.[Richard],
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Nock, R.[Richard], Nielsen, F.[Frank],
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Nielsen, F.[Frank], Nock, R.[Richard],
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Elsevier DOI 0606
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Elsevier DOI 0611
Data mining; Classifier combination; Genetic algorithms BibRef

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IEEE DOI 0711
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PRL(29), No. 11, 1 August 2008, pp. 1632-1638.
Elsevier DOI 0804
Grouping; Pairwise clustering; Hierarchical clustering; Graph algorithms 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.],
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IEEE DOI 0910
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Li, X.T.[Xu-Tao], Ye, Y.M.[Yun-Ming], Li, M.J.J.[Mark Jun-Jie], Ng, M.K.[Michael K.],
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PR(43), No. 9, September 2010, pp. 3130-3143.
Elsevier DOI 1006
Hierarchical clustering; Multi-densities; Cluster tree; k-Means-type algorithm BibRef

Tang, X.Q.[Xu-Qing], Zhu, P.[Ping], Cheng, J.X.[Jia-Xing],
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PR(43), No. 11, November 2010, pp. 3768-3786.
Elsevier DOI 1008
Granular computing; Granular space; Normalized metric space; Clustering structural analysis; Consistent cluster; Optimal cluster; Clustering fusion BibRef

Perina, A.[Alessandro], Cristani, M.[Marco], Castellani, U.[Umberto], Murino, V.[Vittorio], Jojic, N.[Nebojsa],
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IEEE DOI 1205
Hybrid generative/discriminative paradigm, variational free energy, classification. Fixed dimension feature vector for each data sample of varying size. BibRef

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PRL(34), No. 2, 15 January 2013, pp. 155-162.
Elsevier DOI 1212
Data mining; Agglomerative clustering; Heuristic; Blurring; Top-down; Structural nearest neighbor BibRef

Pérez-Suárez, A.[Airel], Martínez-Trinidad, J.F.[José Francisco], Carrasco-Ochoa, J.A.[Jesús A.], Medina-Pagola, J.E.[José E.],
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Elsevier DOI 1306
Data mining; Clustering; Overlapping clustering algorithms; Dynamic clustering algorithms BibRef

Zhang, W.[Wei], Zhao, D.L.[De-Li], Wang, X.G.[Xiao-Gang],
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Elsevier DOI 1306
Agglomerative clustering; Path integral; Graph algorithms; Random walk BibRef

Kim, B.S.[Byung-Soo], Park, J.Y.[Jae Young], Gilbert, A.C.[Anna C.], Savarese, S.[Silvio],
Hierarchical classification of images by sparse approximation,
IVC(31), No. 12, 2013, pp. 982-991.
Elsevier DOI 1312
Sparse approximation BibRef

Kim, B.S.[Byung Soo], Park, J.Y.[Jae Young], Mohan, A.[Anush], Gilbert, A.C.[Anna C.], Savarese, S.[Silvio],
Hierarchical Classification of Images by Sparse Approximation 1,
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Abin, A.A.[Ahmad Ali], Beigy, H.[Hamid],
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Elsevier DOI 1312
Active constraint selection BibRef

Abin, A.A.[Ahmad Ali], Beigy, H.[Hamid],
Active constrained fuzzy clustering: A multiple kernels learning approach,
PR(48), No. 3, 2015, pp. 953-967.
Elsevier DOI 1412
Constrained clustering BibRef

Lotfi, A.[Abdulrahman], Moradi, P.[Parham], Beigy, H.[Hamid],
Density peaks clustering based on density backbone and fuzzy neighborhood,
PR(107), 2020, pp. 107449.
Elsevier DOI 2008
Fuzzy kernel, Density peaks clustering, Noise detection, Label propagation BibRef

Abin, A.A.[Ahmad Ali],
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Elsevier DOI 1612
Constrained clustering BibRef

Sharmila, T.S.[T. Sree], Ramar, K., Raja, T.S.R.[T. Sree Renga],
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SIViP(8), No. 1, January 2014, pp. 149-157.
WWW Link. 1402
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Zhu, S.[Shiai], Wei, X.Y.[Xiao-Yong], Ngo, C.W.[Chong-Wah],
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Elsevier DOI 1406
Concept detection BibRef

Huang, X., Lu, Q., Zhang, L., Plaza, A.,
New Postprocessing Methods for Remote Sensing Image Classification: A Systematic Study,
GeoRS(52), No. 11, November 2014, pp. 7140-7159.
IEEE DOI 1407
Anisotropic magnetoresistance BibRef

Huang, S.J.[Sheng-Jun], Jin, R.[Rong], Zhou, Z.H.[Zhi-Hua],
Active Learning by Querying Informative and Representative Examples,
PAMI(36), No. 10, October 2014, pp. 1936-1949.
IEEE DOI 1410
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Espinola, M., Piedra-Fernandez, J.A., Ayala, R., Iribarne, L., Wang, J.Z.,
Contextual and Hierarchical Classification of Satellite Images Based on Cellular Automata,
GeoRS(53), No. 2, February 2015, pp. 795-809.
IEEE DOI 1411
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de Morsier, F.[Frank], Tuia, D.[Devis], Borgeaud, M.[Maurice], Gass, V.[Volker], Thiran, J.P.[Jean-Philippe],
Cluster validity measure and merging system for hierarchical clustering considering outliers,
PR(48), No. 4, 2015, pp. 1478-1489.
Elsevier DOI 1502
Clustering BibRef

de Morsier, F.[Frank], Borgeaud, M.[Maurice], Gass, V.[Volker], Thiran, J.P.[Jean-Philippe], Tuia, D.[Devis],
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GeoRS(54), No. 6, June 2016, pp. 3410-3420.
IEEE DOI 1606
hyperspectral imaging BibRef

Leski, J.M.[Jacek M.], Kotas, M.[Marian],
Hierarchical clustering with planar segments as prototypes,
PRL(54), No. 1, 2015, pp. 1-10.
Elsevier DOI 1502
Hierarchical clustering BibRef

Mall, R.[Raghvendra], Mehrkanoon, S.[Siamak], Suykens, J.A.K.[Johan A.K.],
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PRL(55), No. 1, 2015, pp. 1-7.
Elsevier DOI 1503
Gershgorin circle theorem BibRef

Mehrkanoon, S.[Siamak], Huang, X.L.[Xiao-Lin], Suykens, J.A.K.[Johan A.K.],
Indefinite kernel spectral learning,
PR(78), 2018, pp. 144-153.
Elsevier DOI 1804
Semi-supervised learning, Scalable models, Indefinite kernels, Kernel spectral clustering, Low embedding dimension BibRef

He, M.Z.[Ming-Zhen], He, F.[Fan], Shi, L.[Lei], Huang, X.L.[Xiao-Lin], Suykens, J.A.K.[Johan A. K.],
Learning With Asymmetric Kernels: Least Squares and Feature Interpretation,
PAMI(45), No. 8, August 2023, pp. 10044-10054.
IEEE DOI 2307
Kernel, Support vector machines, Directed graphs, Task analysis, Feature extraction, Matrix decomposition, Symmetric matrices, least squares support vector machine BibRef

Lian, C.F.[Chun-Feng], Ruan, S.[Su], Denœux, T.[Thierry],
An evidential classifier based on feature selection and two-step classification strategy,
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Elsevier DOI 1504
Dempster-Shafer theory BibRef

Zhong, C.M.[Cai-Ming], Yue, X.D.[Xiao-Dong], Lei, J.S.[Jing-Sheng],
Visual hierarchical cluster structure: A refined co-association matrix based visual assessment of cluster tendency,
PRL(59), No. 1, 2015, pp. 48-55.
Elsevier DOI 1505
Hierarchical clustering BibRef

Gillis, N., Kuang, D.[Da], Park, H.S.[Hae-Sun],
Hierarchical Clustering of Hyperspectral Images Using Rank-Two Nonnegative Matrix Factorization,
GeoRS(53), No. 4, April 2015, pp. 2066-2078.
IEEE DOI 1502
feature extraction BibRef

Najjar, A.[Alameen], Ogawa, T.[Takahiro], Haseyama, M.[Miki],
Bregman pooling: feature-space local pooling for image classification,
MultInfoRetr(4), No. 4, December 2015, pp. 247-259.
Springer DOI 1511
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Bakoben, M.[Maha], Bellotti, A.[Anthony], Adams, N.M.[Niall M.],
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PRL(77), No. 1, 2016, pp. 28-34.
Elsevier DOI 1606
Clustering with uncertainty BibRef

Wu, H.[Hang], Liu, B.Z.[Bao-Zhen], Su, W.H.[Wei-Hua], Zhang, W.C.[Wen-Chang], Sun, J.G.[Jing-Gong],
Hierarchical Coding Vectors for Scene Level Land-Use Classification,
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DOI Link 1606
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Alsahwa, B.[Bassem], Solaiman, B.[Basel], Almouahed, S.[Shaban], Bossé, É.[Éloi], Guériot, D.[Didier],
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IP(25), No. 8, August 2016, pp. 3533-3545.
IEEE DOI 1608
Markov processes BibRef

Zhuo, Z.L.[Zhong-Liu], Zhang, X.S.[Xiao-Song], Niu, W.[Weina], Yang, G.W.[Guo-Wu], Zhang, J.Z.[Jing-Zhong],
Improving data field hierarchical clustering using Barnes-Hut algorithm,
PRL(80), No. 1, 2016, pp. 113-120.
Elsevier DOI 1609
Barnes-Hut algorithm BibRef

Hoyoux, T.[Thomas], Rodríguez-Sánchez, A.J.[Antonio J.], Piater, J.H.[Justus H.],
Can Computer Vision Problems Benefit from Structured Hierarchical Classification?,
MVA(27), No. 8, November 2016, pp. 1299-1312.
Springer DOI 1612
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Earlier: Add A4: Szedmak, S.[Sandor], CAIP15(II:403-414).
Springer DOI 1511
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Li, S.N.[Shao-Ning], Li, W.J.[Wen-Jing], Qiu, J.[Jia],
A Novel Divisive Hierarchical Clustering Algorithm for Geospatial Analysis,
IJGI(6), No. 1, 2017, pp. xx-yy.
DOI Link 1702
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Yang, C.X.[Chen-Xue], Ye, M.[Mao], Tang, S.[Song], Xiang, T.[Tao], Liu, Z.J.[Zi-Jian],
Semi-supervised low-rank representation for image classification,
SIViP(11), No. 1, January 2017, pp. 73-80.
Springer DOI 1702
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Cheng, F.Y.[Fei-Yang], He, X.M.[Xu-Ming], Zhang, H.[Hong],
Stacked Learning to Search for Scene Labeling,
IP(26), No. 4, April 2017, pp. 1887-1898.
IEEE DOI 1704
Cost function BibRef

Bertini Junior, J.R.[Joăo Roberto], do Carmo Nicoletti, M.[Maria],
Enhancing classification performance using attribute-oriented functionally expanded data,
PRL(89), No. 1, 2017, pp. 39-45.
Elsevier DOI 1704
Improving classification performance BibRef

Garcia-Piquer, A.[Alvaro], Bacardit, J.[Jaume], Fornells, A.[Albert], Golobardes, E.[Elisabet],
Scaling-up multiobjective evolutionary clustering algorithms using stratification,
PRL(93), No. 1, 2017, pp. 69-77.
Elsevier DOI 1706
Multiobjective evolutionary algorithms BibRef

Wang, L.G.[Lei-Guang], Huang, X.[Xin], Zheng, C.[Chen], Zhang, Y.[Yun],
A Markov random field integrating spectral dissimilarity and class co-occurrence dependency for remote sensing image classification optimization,
PandRS(128), No. 1, 2017, pp. 223-239.
Elsevier DOI 1706
Remote sensing image classification. MRF model for edge-preserving spatial regularization of classification maps. BibRef

Mondal, S.A.[Sakib A.],
An improved approximation algorithm for hierarchical clustering,
PRL(104), 2018, pp. 23-28.
Elsevier DOI 1804
Clustering, Hierarchical, Approximation BibRef

Yang, Y., Li, B., Li, P., Liu, Q.,
A Two-Stage Clustering Based 3D Visual Saliency Model for Dynamic Scenarios,
MultMed(21), No. 4, April 2019, pp. 809-820.
IEEE DOI 1903
Visualization, Solid modeling, Feature extraction, Videos, two-stage clustering BibRef

Oh, K.W.[Ki-Won], Choi, K.S.[Kang-Sun],
Acceleration of simple linear iterative clustering using early candidate cluster exclusion,
RealTimeIP(16), No. 4, August 2019, pp. 945-956.
WWW Link. 1908
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Earlier: A2, A1:
Fast Simple Linear Iterative Clustering by Early Candidate Cluster Elimination,
IbPRIA15(579-586).
Springer DOI 1506
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Whang, J.J.Y.[Joyce Ji-Young], Hou, Y.Y.[Yang-Yang], Gleich, D.F.[David F.], Dhillon, I.S.[Inderjit S.],
Non-Exhaustive, Overlapping Clustering,
PAMI(41), No. 11, November 2019, pp. 2644-2659.
IEEE DOI 1910
Clustering algorithms, Linear programming, Kernel, Iterative methods, Computer science, Anomaly detection, community detection BibRef

Zhang, J.[Jun], Zhang, M.[Min], Shi, L.[Lukui], Yan, W.J.[Wen-Jie], Pan, B.[Bin],
A Multi-Scale Approach for Remote Sensing Scene Classification Based on Feature Maps Selection and Region Representation,
RS(11), No. 21, 2019, pp. xx-yy.
DOI Link 1911
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Huang, L.[Lei], Ma, Y.Q.[Yu-Qing], Liu, X.L.[Xiang-Long],
A general non-parametric active learning framework for classification on multiple manifolds,
PRL(130), 2020, pp. 250-258.
Elsevier DOI 2002
Active learning, Multi-class classification, Label propagation, Non-parametric BibRef

Lamb, D.S.[David S.], Downs, J.[Joni], Reader, S.[Steven],
Space-Time Hierarchical Clustering for Identifying Clusters in Spatiotemporal Point Data,
IJGI(9), No. 2, 2020, pp. xx-yy.
DOI Link 2003
Applies to GIS. BibRef

Hao, X.H.[Xiao-Hui], Wu, Y.[Yiquan], Wang, P.[Peng],
Angle Distance-Based Hierarchical Background Separation Method for Hyperspectral Imagery Target Detection,
RS(12), No. 4, 2020, pp. xx-yy.
DOI Link 2003
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Lin, Q.F.[Qi-Feng], Ling, Q.[Qing],
Decentralized TD(0) With Gradient Tracking,
SPLetters(28), 2021, pp. 723-727.
IEEE DOI 2105
Convergence, Signal processing algorithms, Function approximation, Approximation algorithms, Acceleration, gradient tracking BibRef

Li, M.[Ming], Lei, L.[Lin], Tang, Y.Q.[Yu-Qi], Sun, Y.[Yuli], Kuang, G.Y.[Gang-Yao],
An Attention-Guided Multilayer Feature Aggregation Network for Remote Sensing Image Scene Classification,
RS(13), No. 16, 2021, pp. xx-yy.
DOI Link 2109
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Xie, W.B.[Wen-Bo], Liu, Z.[Zhen], Das, D.[Debarati], Chen, B.[Bin], Srivastava, J.[Jaideep],
Scalable clustering by aggregating representatives in hierarchical groups,
PR(136), 2023, pp. 109230.
Elsevier DOI 2301
Hierarchical clustering, Election tree, Representative node, Root BibRef

del Moral, P.[Pablo], Nowaczyk, S.[Slawomir], Sant'Anna, A.[Anita], Pashami, S.[Sepideh],
Pitfalls of assessing extracted hierarchies for multi-class classification,
PR(136), 2023, pp. 109225.
Elsevier DOI 2301
Hierarchical multi-class classification, Multi-class classification, Class hierarchies BibRef

Han, X.[Xin], Zhu, Y.[Ye], Ting, K.M.[Kai Ming], Li, G.[Gang],
The impact of isolation kernel on agglomerative hierarchical clustering algorithms,
PR(139), 2023, pp. 109517.
Elsevier DOI 2304
Agglomerative hierarchical clustering, Varied densities, Dendrogram purity, Isolation kernel, Gaussian kernel BibRef

Hao, P.Y.[Peng-Yi], Shi, K.J.[Kang-Jian], Tian, S.Y.[Shu-Yuan], Wu, F.[Fuli],
Uncertainty-aware iterative learning for noisy-labeled medical image segmentation,
IET-IPR(17), No. 13, 2023, pp. 3830-3840.
DOI Link 2311
image segmentation, medical image processing BibRef

Zhao, H.H.Y.[Henry Heng-Yuan], Wang, P.[Pichao], Zhao, Y.Y.[Yu-Yang], Luo, H.[Hao], Wang, F.[Fan], Shou, M.Z.[Mike Zheng],
SCT: A Simple Baseline for Parameter-Efficient Fine-Tuning via Salient Channels,
IJCV(132), No. 3, March 2024, pp. 731-749.
Springer DOI 2402
Code:
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Wang, C.K.[Cheng-Kun], Zheng, W.Z.[Wen-Zhao], Zhu, Z.[Zheng], Zhou, J.[Jie], Lu, J.W.[Ji-Wen],
OPERA: Omni-Supervised Representation Learning with Hierarchical Supervisions,
ICCV23(5536-5547)
IEEE DOI 2401
BibRef

An, D.S.[Dong-Sheng], Xie, J.W.[Jian-Wen], Li, P.[Ping],
Learning Deep Latent Variable Models by Short-Run MCMC Inference with Optimal Transport Correction,
CVPR21(15410-15419)
IEEE DOI 2111
Training, Monte Carlo methods, Costs, Image synthesis, Markov processes, Pattern recognition, Task analysis BibRef

Chaudhuri, U.[Ushasi], Chaudhuri, S.[Syomantak], Chaudhuri, S.[Subhasis],
GuCNet: A Guided Clustering-based Network for Improved Classification,
ICPR21(7335-7342)
IEEE DOI 2105
Training, Semantics, Neural networks, Prototypes, Network architecture, Benchmark testing, Topology BibRef

Chen, C.[Chao], Li, G.B.[Guan-Bin], Xu, R.J.[Rui-Jia], Chen, T.S.[Tian-Shui], Wang, M.[Meng], Lin, L.[Liang],
ClusterNet: Deep Hierarchical Cluster Network With Rigorously Rotation-Invariant Representation for Point Cloud Analysis,
CVPR19(4989-4997).
IEEE DOI 2002
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Montaldo, A., Fronda, L., Hedhli, I., Moser, G., Serpico, S.B., Zerubia, J.,
Causal Markov Mesh Hierarchical Modeling for the Contextual Classification of Multiresolution Satellite Images,
ICIP19(2716-2720)
IEEE DOI 1910
Multiresolution images, causality, hierarchical Markov random field, Markov mesh random field, semantic image segmentation BibRef

Saha, S.[Soham], Varma, G.[Girish], Jawahar, C.V.,
Class2Str: End to End Latent Hierarchy Learning,
ICPR18(1000-1005)
IEEE DOI 1812
Feature extraction, Training, Encoding, Entropy, Neural networks, Binary trees, Testing BibRef

José-García, A.[Adán], Gómez-Flores, W.[Wilfrido],
Evolutionary Clustering Using Multi-prototype Representation and Connectivity Criterion,
MCPR17(63-73).
Springer DOI 1706
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Karray, E., Loghmari, M.A., Naceur, M.S.,
High and low-level hierarchical classification as an efficient analysis of remotely sensed hyperpectral data,
ISIVC16(236-241)
IEEE DOI 1704
Hyperspectral imaging BibRef

Klein, D.A.[Dominik Alexander], Schulz, D.[Dirk], Cremers, A.B.[Armin Bernd],
Realtime Hierarchical Clustering Based on Boundary and Surface Statistics,
ACCV16(I: 3-19).
Springer DOI 1704
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Qian, B.[Bin], Shen, X.B.[Xiao-Bo], Gu, Y.Y.[Yan-Yang], Tang, Z.M.[Zhen-Min], Ding, Y.H.[Yu-Hua],
Double Constrained NMF for Partial Multi-View Clustering,
DICTA16(1-7)
IEEE DOI 1701
nonnegative matrix factorization. Clustering methods BibRef

Hedhli, I.[Ihsen], Moser, G.[Gabriele], Serpico, S.B.[Sebastiano B.], Zerubia, J.B.[Josiane B.],
Contextual multi-scale image classification on quadtree,
ICIP16(1349-1353)
IEEE DOI 1610
Analytical models BibRef

Romero, A.R., Jayawardena, S., Cox, M., Borges, P.V.K.,
Partitioning the Input Domain for Classification,
DICTA15(1-8)
IEEE DOI 1603
computational complexity BibRef

Villalon-Turrubiates, I.E.,
A dynamical model to classify the content of multitemporal images employing distributed computing techniques,
MultiTemp15(1-4)
IEEE DOI 1511
Big Data BibRef

Febrer-Hernández, J.K.[José K.], Hernández-León, R.[Raudel], Hernández-Palancarr, J.[José], Feregrino-Uribe, C.[Claudia],
Improving the Accuracy of the Sequential Patterns-Based Classifiers,
CIARP15(708-715).
Springer DOI 1511
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Aroche-Villarruel, A.A.[Argenis A.], Martínez-Trinidad, J.F.[José Francisco], Carrasco-Ochoa, J.A.[Jesús Ariel], Pérez-Suárez, A.[Airel],
A Different Approach for Pruning Micro-clusters in Data Stream Clustering,
MCPR15(33-43).
Springer DOI 1506
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Mustafa, W.[Wail], Kraft, D.[Dirk], Krüger, N.[Norbert],
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IbPRIA15(541-551).
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Tax, D.M.J.[David M.J.], Sontrop, H.M.J.[Herman M.J.], Reinders, M.J.T.[Marcel J.T], Moerland, P.D.[Perry D.],
The Effect of Aggregating Subtype Performances Depends Strongly on the Performance Measure Used,
ICPR14(3720-3725)
IEEE DOI 1412
Accuracy BibRef

Zemene, E.[Eyasu], Alemu, L.T., Pelillo, M.[Marcello],
Constrained dominant sets for retrieval,
ICPR16(2568-2573)
IEEE DOI 1705
Coherence, Databases, Diffusion processes, Face, Manifolds, Optimization BibRef

Zemene, E.[Eyasu], Pelillo, M.[Marcello],
Path-Based Dominant-Set Clustering,
CIAP15(I:150-160).
Springer DOI 1511
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Biggio, B.[Battista], Bulň, S.R.[Samuel Rota], Pillai, I.[Ignazio], Mura, M.[Michele], Zemene Mequanint, E.[Eyasu], Pelillo, M.[Marcello], Roli, F.[Fabio],
Poisoning Complete-Linkage Hierarchical Clustering,
SSSPR14(42-52).
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preventing deliberate attack on clustering algorithm in security application. BibRef

Chandrashekar, V., Kumar, S., Jawahar, C.V.,
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ACPR13(522-526)
IEEE DOI 1408
eigenvalues and eigenfunctions BibRef

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Li, X.[Xin], Guo, Y.H.[Yu-Hong],
Multi-level Adaptive Active Learning for Scene Classification,
ECCV14(VII: 234-249).
Springer DOI 1408
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Earlier:
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CVPR13(859-866)
IEEE DOI 1309
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Earlier:
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BMVC12(81).
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active learning; image classification BibRef

Yenialp, E.[Erdal], Kalkan, H.[Habil], Mete, M.[Mutlu],
Improving Density Based Clustering with Multi-Scale Analysis,
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Pauly, O.[Olivier], Mateus, D.[Diana], Navab, N.[Nassir],
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Zhou, Y.J.[Yu-Jin], Tan, Y.H.[Yi-Hua], Li, H.T.[Hai-Tao], Gu, H.Y.[Hai-Yan],
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Aghagolzadeh, M., Soltanian-Zadeh, H., Araabi, B., Aghagolzadeh, A.,
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ICIP07(I: 277-280).
IEEE DOI 0709
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Sakai, T.[Tomoya], Imiya, A.[Atsushi],
Validation of Watershed Regions by Scale-Space Statistics,
SSVM09(175-186).
Springer DOI 0906
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Statistically Valid Graph Representations of Scale-Space Geometry,
ICISP08(338-345).
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Sakai, T.[Tomoya],
Multiple pattern classification by sparse subspace decomposition,
Subspace09(170-177).
IEEE DOI 0910
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Sakai, T.[Tomoya],
Monte Carlo subspace method: An incremental approach to high-dimensional data classification,
ICPR08(1-4).
IEEE DOI 0812
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Sakai, T.[Tomoya], Komazaki, T.[Takuto], Imiya, A.[Atsushi],
Scale-Space Clustering with Recursive Validation,
SSVM07(288-299).
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Karadag, O.O.[Ozge Oztimur], Vural, F.T.Y.[Fatos T. Yarman],
HANOLISTIC: A Hierarchical Automatic Image Annotation System Using Holistic Approach,
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CVPR07(1-8).
IEEE DOI 0706
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Gagrani, A.[Aakanksha], Gupta, L.[Lalit], Ravindran, B., Das, S.[Sukhendu], Roychowdhury, P.[Pinaki], Panchal, V.K.,
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ICPR06(II: 833-836).
IEEE DOI 0609
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ICPR06(I: 900-903).
IEEE DOI 0609
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Spectral Methods for Automatic Multiscale Data Clustering,
CVPR06(I: 190-197).
IEEE DOI 0606
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Zhang, K.[Kai], Tang, M.[Ming], Kwok, J.T.[James T.],
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Carrivick, L.[Luke], Prabhu, S.[Sanjay], Goddard, P.[Paul], Rossiter, J.[Jonathan],
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IEEE DOI 0211
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Rendon, E., Barandela, R.,
Fast hierarchical clustering based on compressed data,
ICPR02(II: 216-219).
IEEE DOI 0211
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Zöller, T., Buhmann, J.M.,
Active Learning for Hierarchical Pairwise Data Clustering,
ICPR00(Vol II: 186-189).
IEEE DOI 0009
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Chardin, A., Perez, P.,
Unsupervised Image Classification with a Hierarchical EM Algorithm,
ICCV99(969-974).
IEEE DOI BibRef 9900
Earlier:
Semi-iterative inference with hierarchical models,
ICIP98(I: 630-634).
IEEE DOI 9810
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Schikuta, E.,
Grid-Clustering: An Efficient Hierarchical Clustering Method for Very Large Data Sets,
ICPR96(II: 101-105).
IEEE DOI 9608
(Univ. of Vienna, A) BibRef

Bajcsy, P., Ahuja, N.,
Uniformity and Homogeneity Based Hierarchical Clustering,
ICPR96(II: 96-100).
IEEE DOI 9608
(Univ. of Illinois, Urbana, USA) BibRef

Roberts, S.J.,
Scale-Space Unsupervised Cluster Analysis,
ICPR96(II: 106-110).
IEEE DOI 9608
(Univ. of London, UK) BibRef

Jin, J.S.,
Hierarchical pattern matching using a high entropy signature,
ICPR94(B:436-438).
IEEE DOI 9410
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Prabhu, S.M., Garg, D.P., Spano, Sr., M.R.,
A hierarchical labeled object classification system,
ICPR94(B:479-481).
IEEE DOI 9410
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Jiang, H.T.[Hong-Tao], Bolviken, E.,
A general parameter updating approach to image classification,
ICPR94(A:720-722).
IEEE DOI 9410
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Tseng, C.T., Moret, B.M.E.,
The design of a nonparametric hierarchical classifier,
ICPR90(I: 428-432).
IEEE DOI 9006
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Li, X.,
Hierarchical clustering on SIMD machines with alignment network,
CVPR89(660-665).
IEEE DOI 0403
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Chapter on Pattern Recognition, Clustering, Statistics, Grammars, Learning, Neural Nets, Genetic Algorithms continues in
Dynamic Learning, Incremental Learning .


Last update:Mar 16, 2024 at 20:36:19