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Volumn 54, Issue 1, 2016, Pages 544-557

Unsupervised Band Selection Based on Evolutionary Multiobjective Optimization for Hyperspectral Images

Author keywords

Band selection; evolutionary algorithm (EA); hyperspectral image; multiobjective optimization

Indexed keywords

CLASSIFICATION (OF INFORMATION); DECISION MAKING; EVOLUTIONARY ALGORITHMS; IMAGE PROCESSING; INDEPENDENT COMPONENT ANALYSIS; OPTIMIZATION; SET THEORY; SPECTROSCOPY;

EID: 84947027877     PISSN: 01962892     EISSN: None     Source Type: Journal    
DOI: 10.1109/TGRS.2015.2461653     Document Type: Article
Times cited : (160)

References (64)
  • 2
    • 84906306228 scopus 로고    scopus 로고
    • Fast hyperspectral anomaly detection via high-order 2-D crossing filter
    • Feb.
    • Y. Yuan, Q. Wang, and G. Zhu, "Fast hyperspectral anomaly detection via high-order 2-D crossing filter," IEEE Trans. Geosci. Remote Sens., vol. 53, no. 4, pp. 620-630, Feb. 2015.
    • (2015) IEEE Trans. Geosci. Remote Sens. , vol.53 , Issue.4 , pp. 620-630
    • Yuan, Y.1    Wang, Q.2    Zhu, G.3
  • 3
    • 77954647676 scopus 로고    scopus 로고
    • Detection and analysis of the intestinal ischemia using visible and invisible hyperspectral imaging
    • Aug.
    • H. Akbari, Y. Kosugi, K. Kojima, and N. Tanaka, "Detection and analysis of the intestinal ischemia using visible and invisible hyperspectral imaging," IEEE Trans. Biomed. Eng., vol. 57, no. 8, pp. 2011-2017, Aug. 2010.
    • (2010) IEEE Trans. Biomed. Eng. , vol.57 , Issue.8 , pp. 2011-2017
    • Akbari, H.1    Kosugi, Y.2    Kojima, K.3    Tanaka, N.4
  • 4
    • 84906782734 scopus 로고    scopus 로고
    • Hierarchical change detection in multitemporal hyperspectral images
    • Jan.
    • S. Liu, L. Bruzzone, F. Bovolo, and P. Du, "Hierarchical change detection in multitemporal hyperspectral images," IEEE Trans. Geosci. Remote Sens., vol. 53, no. 1, pp. 244-260, Jan. 2015.
    • (2015) IEEE Trans. Geosci. Remote Sens. , vol.53 , Issue.1 , pp. 244-260
    • Liu, S.1    Bruzzone, L.2    Bovolo, F.3    Du, P.4
  • 5
    • 77957741951 scopus 로고
    • On the mean accuracy of statistical pattern recognizers
    • Jan.
    • G. F. Hughes, "On the mean accuracy of statistical pattern recognizers," IEEE Trans. Inf. Theroy, vol. 14, no. 1, pp. 55-63, Jan. 1968.
    • (1968) IEEE Trans. Inf. Theroy , vol.14 , Issue.1 , pp. 55-63
    • Hughes, G.F.1
  • 6
    • 14644435059 scopus 로고    scopus 로고
    • Dimensionality reduction and classification of hyperspectral image data using sequences of extended morphological transformations
    • Mar.
    • A. Plaza, P. Martinez, J. Plaza, and R. Perez, "Dimensionality reduction and classification of hyperspectral image data using sequences of extended morphological transformations," IEEE Trans. Geosci. Remote Sens., vol. 43, no. 3, pp. 466-479, Mar. 2005.
    • (2005) IEEE Trans. Geosci. Remote Sens. , vol.43 , Issue.3 , pp. 466-479
    • Plaza, A.1    Martinez, P.2    Plaza, J.3    Perez, R.4
  • 7
    • 33744726231 scopus 로고    scopus 로고
    • Constrained band selection for hyperspectral imagery
    • Jun.
    • C.-I. Chang and S. Wang, "Constrained band selection for hyperspectral imagery," IEEE Trans. Geosci. Remote Sens., vol. 44, no. 6, pp. 1575-1585, Jun. 2006.
    • (2006) IEEE Trans. Geosci. Remote Sens. , vol.44 , Issue.6 , pp. 1575-1585
    • Chang, C.-I.1    Wang, S.2
  • 9
    • 33744719449 scopus 로고    scopus 로고
    • Independent component analysis-based dimensionality reduction with applications in hyperspectral image analysis
    • Jun.
    • J.Wang and C.-I. Chang, "Independent component analysis-based dimensionality reduction with applications in hyperspectral image analysis," IEEE Trans.Geosci. Remote Sens., vol. 44, no. 6, pp. 1586-1600, Jun. 2006.
    • (2006) IEEE Trans.Geosci. Remote Sens. , vol.44 , Issue.6 , pp. 1586-1600
    • Wang, J.1    Chang, C.-I.2
  • 10
    • 84859784358 scopus 로고    scopus 로고
    • Locality-preserving dimensionality reduction and classification for hyperspectral image analysis
    • Apr.
    • W. Lei, S. Prasad, J. E. Fowler, and L. M. Bruce, "Locality-preserving dimensionality reduction and classification for hyperspectral image analysis," IEEE Trans. Geosci. Remote Sens., vol. 50, no. 4, pp. 1185-1198, Apr. 2012.
    • (2012) IEEE Trans. Geosci. Remote Sens. , vol.50 , Issue.4 , pp. 1185-1198
    • Lei, W.1    Prasad, S.2    Fowler, J.E.3    Bruce, L.M.4
  • 11
    • 79952901555 scopus 로고    scopus 로고
    • Supervised Gaussian process latent variable model for dimensionality reduction
    • Apr.
    • X. Gao, X.Wang, D. Tao, and X. Li, "Supervised Gaussian process latent variable model for dimensionality reduction," IEEE Trans. Syst., Man, Cybern. B, Cybern., vol. 41, no. 2, pp. 425-434, Apr. 2011.
    • (2011) IEEE Trans. Syst., Man, Cybern. B, Cybern. , vol.41 , Issue.2 , pp. 425-434
    • Gao, X.1    Wang, X.2    Tao, D.3    Li, X.4
  • 12
    • 0034704222 scopus 로고    scopus 로고
    • Nonlinear dimensionality reduction by locally linear embedding
    • Dec.
    • S. T. Roweis and L. K. Saul, "Nonlinear dimensionality reduction by locally linear embedding," Science, vol. 90, no. 5500, pp. 2323-2326, Dec. 2000.
    • (2000) Science , vol.90 , Issue.5500 , pp. 2323-2326
    • Roweis, S.T.1    Saul, L.K.2
  • 13
    • 84901250680 scopus 로고    scopus 로고
    • Joint embedding learning and sparse regression: A framework for unsupervised feature selection
    • Jun.
    • C. Hou, F. Nie, X. Li, D. Yi, and Y. Wu, "Joint embedding learning and sparse regression: A framework for unsupervised feature selection," IEEE Trans. Cybern., vol. 44, no. 6, pp. 793-804, Jun. 2014.
    • (2014) IEEE Trans. Cybern. , vol.44 , Issue.6 , pp. 793-804
    • Hou, C.1    Nie, F.2    Li, X.3    Yi, D.4    Wu, Y.5
  • 14
    • 84893654461 scopus 로고    scopus 로고
    • Locality and similarity preserving embedding for feature selection
    • Mar.
    • X. Fang et al., "Locality and similarity preserving embedding for feature selection," Neurocomputing, vol. 128, pp. 304-315, Mar. 2014.
    • (2014) Neurocomputing , vol.128 , pp. 304-315
    • Fang, X.1
  • 15
    • 33750590333 scopus 로고    scopus 로고
    • Band selection for hyperspectral image classification using mutual information
    • Oct.
    • B. Guo, S. R. Gunn, R. I. Damper, and J. D. B. Nelson, "Band selection for hyperspectral image classification using mutual information," IEEE Geosci. Remote Sens. Lett., vol. 3, no. 4, pp. 522-526, Oct. 2006.
    • (2006) IEEE Geosci. Remote Sens. Lett. , vol.3 , Issue.4 , pp. 522-526
    • Guo, B.1    Gunn, S.R.2    Damper, R.I.3    Nelson, J.D.B.4
  • 16
    • 36349016757 scopus 로고    scopus 로고
    • Dimensionality reduction based on clonal selection for hyperspectral imagery
    • Dec.
    • L. Zhang, Y. Zhong, B. Huang, J. Gong, and P. Li, "Dimensionality reduction based on clonal selection for hyperspectral imagery," IEEE Trans. Geosci. Remote Sens., vol. 45, no. 12, pp. 4172-4186, Dec. 2007.
    • (2007) IEEE Trans. Geosci. Remote Sens. , vol.45 , Issue.12 , pp. 4172-4186
    • Zhang, L.1    Zhong, Y.2    Huang, B.3    Gong, J.4    Li, P.5
  • 17
    • 0029407869 scopus 로고
    • An extension of the Jeffreys-Matusita distance to multiclass cases for feature selection
    • Nov.
    • L. Bruzzone, F. Roli, and S. B. Serpico, "An extension of the Jeffreys-Matusita distance to multiclass cases for feature selection," IEEE Trans. Geosci. Remote Sens., vol. 33, no. 6, pp. 1318-1321, Nov. 1995.
    • (1995) IEEE Trans. Geosci. Remote Sens. , vol.33 , Issue.6 , pp. 1318-1321
    • Bruzzone, L.1    Roli, F.2    Serpico, S.B.3
  • 18
    • 0024895461 scopus 로고
    • A note on genetic algorithms for large scale feature selection
    • Nov.
    • W. Siedlecki and J. Sklansky, "A note on genetic algorithms for large scale feature selection," Pattern Recognit. Lett., vol. 10, no. 5, pp. 335-347, Nov. 1989.
    • (1989) Pattern Recognit. Lett. , vol.10 , Issue.5 , pp. 335-347
    • Siedlecki, W.1    Sklansky, J.2
  • 19
    • 84896394026 scopus 로고    scopus 로고
    • Hyperspectral band selection based on trivariate mutual information and clonal selection
    • Jul.
    • J. Feng, L. C. Jiao, X. Zhang, and T. Sun, "Hyperspectral band selection based on trivariate mutual information and clonal selection," IEEE Trans. Geosci. Remote Sens., vol. 52, no. 7, pp. 4092-4105, Jul. 2014.
    • (2014) IEEE Trans. Geosci. Remote Sens. , vol.52 , Issue.7 , pp. 4092-4105
    • Feng, J.1    Jiao, L.C.2    Zhang, X.3    Sun, T.4
  • 20
    • 0023854011 scopus 로고
    • A transformation for ordering multispectral data in terms of image quality with implications for noise removal
    • Jan.
    • A. A. Green, M. Berman, P. Switzer, and M. D. Craig, "A transformation for ordering multispectral data in terms of image quality with implications for noise removal," IEEE Trans. Geosci. Remote Sens., vol. 26, no. 1, pp. 65-74, Jan. 1988.
    • (1988) IEEE Trans. Geosci. Remote Sens. , vol.26 , Issue.1 , pp. 65-74
    • Green, A.A.1    Berman, M.2    Switzer, P.3    Craig, M.D.4
  • 21
    • 0025430387 scopus 로고
    • Enhancement of high spectral resolution remote sensing data by a noise-adjusted principal components transform
    • May
    • J. B. Lee, A. S. Woodyatt, and M. Berman, "Enhancement of high spectral resolution remote sensing data by a noise-adjusted principal components transform," IEEE Trans. Geosci. Remote Sens., vol. 28, no. 3, pp. 295-304, May 1990.
    • (1990) IEEE Trans. Geosci. Remote Sens. , vol.28 , Issue.3 , pp. 295-304
    • Lee, J.B.1    Woodyatt, A.S.2    Berman, M.3
  • 22
    • 0028545567 scopus 로고
    • A fast way to compute the noise-adjusted principal components transform matrix
    • Nov.
    • R. E. Roger, "A fast way to compute the noise-adjusted principal components transform matrix," IEEE Trans. Geosci. Remote Sens., vol. 32, no. 6, pp. 1194-1196, Nov. 1994.
    • (1994) IEEE Trans. Geosci. Remote Sens. , vol.32 , Issue.6 , pp. 1194-1196
    • Roger, R.E.1
  • 23
    • 0033224770 scopus 로고    scopus 로고
    • A joint band prioritization and band decorrelation approach to band selection for hyperspectral image classification
    • Nov.
    • C.-I. Chang, Q. Du, T. S. Sun, and M. L. G. Althouse, "A joint band prioritization and band decorrelation approach to band selection for hyperspectral image classification," IEEE Trans. Geosci. Remote Sens., vol. 37, no. 6, pp. 2631-2641, Nov. 1999.
    • (1999) IEEE Trans. Geosci. Remote Sens. , vol.37 , Issue.6 , pp. 2631-2641
    • Chang, C.-I.1    Du, Q.2    Sun, T.S.3    Althouse, M.L.G.4
  • 24
    • 80255133257 scopus 로고    scopus 로고
    • Semisupervised band clustering for dimensionality reduction of hyperspectral imagery
    • Nov.
    • H. J. Su, H. Yang, Q. Du, and Y. H. Sheng, "Semisupervised band clustering for dimensionality reduction of hyperspectral imagery," IEEE Geosci. Remote Sens. Lett., vol. 8, no. 6, pp. 1135-1139, Nov. 2011.
    • (2011) IEEE Geosci. Remote Sens. Lett. , vol.8 , Issue.6 , pp. 1135-1139
    • Su, H.J.1    Yang, H.2    Du, Q.3    Sheng, Y.H.4
  • 25
    • 84939552975 scopus 로고    scopus 로고
    • Unsupervised cluster-based band selection for hyperspectral image classification
    • Beijing, China, Jul.
    • G. C. T. Jee and C. Wu, "Unsupervised cluster-based band selection for hyperspectral image classification," in Proc. ICACSEI, Beijing, China, Jul. 2013 pp. 562-565.
    • (2013) Proc. ICACSEI , pp. 562-565
    • Jee, G.C.T.1    Wu, C.2
  • 26
    • 36348942491 scopus 로고    scopus 로고
    • Clustering based hyperspectral band selection using information measures
    • Dec.
    • A. M. Usó, F. Pla, J. M. Sotoca, and P. Garciá-Sevilla, "Clustering based hyperspectral band selection using information measures," IEEE Trans. Geosci. Remote Sens., vol. 45, no. 12, pp. 4158-4171, Dec. 2007.
    • (2007) IEEE Trans. Geosci. Remote Sens. , vol.45 , Issue.12 , pp. 4158-4171
    • Usó, A.M.1    Pla, F.2    Sotoca, J.M.3    Garciá-Sevilla, P.4
  • 27
    • 84861735806 scopus 로고    scopus 로고
    • Unsupervised band selection for hyperspectral imagery classification without manual band removal
    • Apr.
    • S. Jia, Z. Ji, Y. Qian, and L. Shen, "Unsupervised band selection for hyperspectral imagery classification without manual band removal," IEEE J. Sel. Topics Appl. Earth Observ., vol. 5, no. 2, pp. 531-543, Apr. 2012.
    • (2012) IEEE J. Sel. Topics Appl. Earth Observ. , vol.5 , Issue.2 , pp. 531-543
    • Jia, S.1    Ji, Z.2    Qian, Y.3    Shen, L.4
  • 28
    • 84906948715 scopus 로고    scopus 로고
    • A new sparsity-based band selection method for target detection of hyperspectral image
    • Feb.
    • K. Sun, X. Geng, and L. Ji, "A new sparsity-based band selection method for target detection of hyperspectral image," IEEE Geosci. Remote Sens. Lett., vol. 12, no. 2, pp. 329-333, Feb. 2015.
    • (2015) IEEE Geosci. Remote Sens. Lett. , vol.12 , Issue.2 , pp. 329-333
    • Sun, K.1    Geng, X.2    Ji, L.3
  • 29
    • 84905914071 scopus 로고    scopus 로고
    • A new band selection method for hyperspectral image based on data quality
    • Jun.
    • K. Sun, X. Geng, L. Ji, and Y. Lu, "A new band selection method for hyperspectral image based on data quality," IEEE J. Sel. Topics Appl. Earth Observ., vol. 7, no. 6, pp. 2697-2703, Jun. 2014.
    • (2014) IEEE J. Sel. Topics Appl. Earth Observ. , vol.7 , Issue.6 , pp. 2697-2703
    • Sun, K.1    Geng, X.2    Ji, L.3    Lu, Y.4
  • 30
    • 84940644968 scopus 로고
    • A mathematical theory of communication
    • Jul.-Oct.
    • E. Shannon, "A mathematical theory of communication," Bell Syst. Tech. J., vol. 27, no. 3, pp. 379-423, Jul.-Oct. 1948.
    • (1948) Bell Syst. Tech. J. , vol.27 , Issue.3 , pp. 379-423
    • Shannon, E.1
  • 32
    • 84896388438 scopus 로고    scopus 로고
    • Unsupervised feature selection using geometrical measures in prototype space for hyperspectral imagery
    • Jul.
    • M. Ghamary Asl, M. R. Mobasheri, and B. Mojaradi, "Unsupervised feature selection using geometrical measures in prototype space for hyperspectral imagery," IEEE Trans. Geosci. Remote Sens., vol. 52, no. 7, pp. 3774-3787, Jul. 2014.
    • (2014) IEEE Trans. Geosci. Remote Sens. , vol.52 , Issue.7 , pp. 3774-3787
    • Ghamary Asl, M.1    Mobasheri, M.R.2    Mojaradi, B.3
  • 33
    • 85076199127 scopus 로고
    • Dimensionality reduction by optimal band selection for pixel classification of hyperspectral imagery
    • Oct.
    • S. D. Stearns, B. E. Wilson, and J. R. Peterson, "Dimensionality reduction by optimal band selection for pixel classification of hyperspectral imagery," in Proc. 16th SPIE, Appl. Digit. Image Process., Oct. 1993, vol. 2028, pp. 118-127.
    • (1993) Proc. 16th SPIE, Appl. Digit. Image Process. , vol.2028 , pp. 118-127
    • Stearns, S.D.1    Wilson, B.E.2    Peterson, J.R.3
  • 34
    • 84902104255 scopus 로고    scopus 로고
    • A fast volume-gradient-based band selection method for hyperspectral image
    • Nov.
    • X. Geng, K. Sun, L. Ji, and Y. Zhao, "A fast volume-gradient-based band selection method for hyperspectral image," IEEE Trans. Geosci. Remote Sens., vol. 52, no. 11, pp. 7111-7119, Nov. 2014.
    • (2014) IEEE Trans. Geosci. Remote Sens. , vol.52 , Issue.11 , pp. 7111-7119
    • Geng, X.1    Sun, K.2    Ji, L.3    Zhao, Y.4
  • 35
    • 84906781720 scopus 로고    scopus 로고
    • Unsupervised band selection by integrating the overall accuracy and redundancy
    • Jan.
    • C. Sui, Y. Tian, Y. Xu, and Y. Xie, "Unsupervised band selection by integrating the overall accuracy and redundancy," IEEE Geosci. Remote Sens. Lett., vol. 12, no. 1, pp. 185-189, Jan. 2015.
    • (2015) IEEE Geosci. Remote Sens. Lett. , vol.12 , Issue.1 , pp. 185-189
    • Sui, C.1    Tian, Y.2    Xu, Y.3    Xie, Y.4
  • 36
    • 55649124564 scopus 로고    scopus 로고
    • Similarity-based unsupervised band selection for hyperspectral image analysis
    • Oct.
    • Q. Du, and H. Yang, "Similarity-based unsupervised band selection for hyperspectral image analysis," IEEE Geosci. Remote Sens. Lett., vol. 5, no. 4, pp. 564-568, Oct. 2008.
    • (2008) IEEE Geosci. Remote Sens. Lett. , vol.5 , Issue.4 , pp. 564-568
    • Du, Q.1    Yang, H.2
  • 37
    • 84906307287 scopus 로고    scopus 로고
    • Hyperspectral band selection by multitask sparsity pursuit
    • Feb.
    • Y. Yuan, G. Zhu, and Q. Wang, "Hyperspectral band selection by multitask sparsity pursuit," IEEE Trans. Geosci. Remote Sens., vol. 53, no. 2, pp. 631-644, Feb. 2015.
    • (2015) IEEE Trans. Geosci. Remote Sens. , vol.53 , Issue.2 , pp. 631-644
    • Yuan, Y.1    Zhu, G.2    Wang, Q.3
  • 38
    • 84892438392 scopus 로고    scopus 로고
    • Progressive band selection of spectral unmixing for hyperspectral imagery
    • Apr.
    • C.-I. Chang and K. Liu, "Progressive band selection of spectral unmixing for hyperspectral imagery," IEEE Trans. Geosci. Remote Sens., vol. 52, no. 4, pp. 2002-2017, Apr. 2014.
    • (2014) IEEE Trans. Geosci. Remote Sens. , vol.52 , Issue.4 , pp. 2002-2017
    • Chang, C.-I.1    Liu, K.2
  • 42
    • 0002629429 scopus 로고
    • An overview of evolutionary algorithms inmultiobjective optimization
    • C. M. Fonseca and P. J. Fleming, "An overview of evolutionary algorithms inmultiobjective optimization,"Evol.Comput., vol. 3, no. 1, pp. 1-16, 1995.
    • (1995) Evol.Comput. , vol.3 , Issue.1 , pp. 1-16
    • Fonseca, C.M.1    Fleming, P.J.2
  • 43
    • 0000599395 scopus 로고
    • Multiple objective optimization with vector evaluated genetic algorithms
    • Ed. Hillsdale, NJ, USA: Lawrence Erlbaum
    • J. D. Schaffer, "Multiple objective optimization with vector evaluated genetic algorithms," in Proc. 1st Int. Conf. Genetic Algorithms, J. J. Grefensttete, Ed. Hillsdale, NJ, USA: Lawrence Erlbaum, 1987, pp. 93-100.
    • (1987) Proc. 1st Int. Conf. Genetic Algorithms, J. J. Grefensttete , pp. 93-100
    • Schaffer, J.D.1
  • 44
    • 0036530772 scopus 로고    scopus 로고
    • A fast and elitist multiobjective genetic algorithm: NSGA-II
    • Apr.
    • K. Deb, S. Agrawal, A. Pratap, and T. Meyarivan, "A fast and elitist multiobjective genetic algorithm: NSGA-II," IEEE Trans. Evol. Comput., vol. 6, no. 2, pp. 182-197, Apr. 2002.
    • (2002) IEEE Trans. Evol. Comput. , vol.6 , Issue.2 , pp. 182-197
    • Deb, K.1    Agrawal, S.2    Pratap, A.3    Meyarivan, T.4
  • 45
    • 3142756516 scopus 로고    scopus 로고
    • Handling multiple objectives with particle swarm optimization
    • Jun.
    • C. A. C. Coello, G. T. Pulido, and M. S. Lechuga, "Handling multiple objectives with particle swarm optimization," IEEE Trans. Evol. Comput., vol. 8, no. 3, pp. 256-279, Jun. 2004.
    • (2004) IEEE Trans. Evol. Comput. , vol.8 , Issue.3 , pp. 256-279
    • Coello, C.A.C.1    Pulido, G.T.2    Lechuga, M.S.3
  • 46
    • 84901404865 scopus 로고    scopus 로고
    • The Pareto archived evolution strategy: A new baseline algorithm for multiobjective optimisation
    • Washington, DC, USA, Jul.
    • J. Knowles and D. Corne, "The Pareto archived evolution strategy: A new baseline algorithm for multiobjective optimisation," in Proc. Congr. Evol. Comput., Washington, DC, USA, Jul. 1999, pp. 98-105.
    • (1999) Proc. Congr. Evol. Comput. , pp. 98-105
    • Knowles, J.1    Corne, D.2
  • 47
    • 2942547409 scopus 로고    scopus 로고
    • SPEA2: Improving the strength Pareto evolutionary algorithm for multiobjective optimization
    • K. C. Giannakoglou, D. T. Tsahalis, J. Périaux, K. D. Papailiou, and T. Fogarty, Eds., Athens, Greece
    • E. Zitzler, M. Laumanns, and L. Thiele, "SPEA2: Improving the strength Pareto evolutionary algorithm for multiobjective optimization," in Proc. Evol. Methods Des. Optim. Control Appl. Ind. Problems, K. C. Giannakoglou, D. T. Tsahalis, J. Périaux, K. D. Papailiou, and T. Fogarty, Eds., Athens, Greece, 2001, pp. 95-100.
    • (2001) Proc. Evol. Methods Des. Optim. Control Appl. Ind. Problems , pp. 95-100
    • Zitzler, E.1    Laumanns, M.2    Thiele, L.3
  • 48
    • 34548108555 scopus 로고    scopus 로고
    • MOEA/D: A multi-objective evolutionary algorithm based on decomposition
    • Dec.
    • Q. Zhang and H. Li, "MOEA/D: A multi-objective evolutionary algorithm based on decomposition," IEEE Trans. Evol. Comput., vol. 11, no. 6, pp. 712-731, Dec. 2007.
    • (2007) IEEE Trans. Evol. Comput. , vol.11 , Issue.6 , pp. 712-731
    • Zhang, Q.1    Li, H.2
  • 49
    • 70549090027 scopus 로고    scopus 로고
    • Clustering of hyperspectral images based on multiobjective particle swarm optimization
    • Dec.
    • A. Paoli, F. Melgani, and E. Pasolli, "Clustering of hyperspectral images based on multiobjective particle swarm optimization," IEEE Trans. Geosci. Remote Sens., vol. 47, no. 12, pp. 4175-4188, Dec. 2009.
    • (2009) IEEE Trans. Geosci. Remote Sens. , vol.47 , Issue.12 , pp. 4175-4188
    • Paoli, A.1    Melgani, F.2    Pasolli, E.3
  • 50
    • 33749867996 scopus 로고    scopus 로고
    • A distributed cooperative coevolutionary algorithm for multiobjective optimization
    • Oct.
    • K. C. Tan, Y. J. Yang, and C. K. Goh, "A distributed cooperative coevolutionary algorithm for multiobjective optimization," IEEE Trans. Evol. Comput., vol. 10, no. 5, pp. 527-549, Oct. 2006.
    • (2006) IEEE Trans. Evol. Comput. , vol.10 , Issue.5 , pp. 527-549
    • Tan, K.C.1    Yang, Y.J.2    Goh, C.K.3
  • 51
    • 59749105367 scopus 로고    scopus 로고
    • A competitive-cooperative coevolutionary paradigm for dynamic multiobjective optimization
    • Feb.
    • C. K. Goh and K. C. Tan, "A competitive-cooperative coevolutionary paradigm for dynamic multiobjective optimization," IEEE Trans. Evol. Comput., vol. 13, no. 1, pp. 103-127, Feb. 2009.
    • (2009) IEEE Trans. Evol. Comput. , vol.13 , Issue.1 , pp. 103-127
    • Goh, C.K.1    Tan, K.C.2
  • 52
    • 0034153728 scopus 로고    scopus 로고
    • Cooperative coevolution: An architecture for evolving coadapted subcomponents
    • M. A. Potter and K. A. De Jong, "Cooperative coevolution: An architecture for evolving coadapted subcomponents," Evol. Comput., vol. 8, no. 1, pp. 1-29, 2000.
    • (2000) Evol. Comput. , vol.8 , Issue.1 , pp. 1-29
    • Potter, M.A.1    De Jong, K.A.2
  • 53
    • 84945243929 scopus 로고    scopus 로고
    • Methodology for hyperspectral band and classification model selection
    • Greenbelt, MD, USA
    • P. Groves and P. Bajcsy, "Methodology for hyperspectral band and classification model selection," in Proc. IEEE Workshop Adv. Tech. Anal. Remotely Sens. Data, Greenbelt, MD, USA, 2003, pp. 120-128.
    • (2003) Proc. IEEE Workshop Adv. Tech. Anal. Remotely Sens. Data , pp. 120-128
    • Groves, P.1    Bajcsy, P.2
  • 54
    • 4143064738 scopus 로고    scopus 로고
    • Methodology for hyperspectral band selection
    • Jul.
    • P. Bajcsy and P. Groves, "Methodology for hyperspectral band selection," Photogramm. Eng. Remote Sens. J., vol. 70, no. 7, pp. 793-802, Jul. 2004.
    • (2004) Photogramm. Eng. Remote Sens. J. , vol.70 , Issue.7 , pp. 793-802
    • Bajcsy, P.1    Groves, P.2
  • 55
    • 2442535151 scopus 로고    scopus 로고
    • Survey of multi-objective optimization methods for engineering
    • Apr.
    • R. T. Marler and J. S. Arora, "Survey of multi-objective optimization methods for engineering," Struct. Multidiscipl. Optim., vol. 26, no. 6, pp. 369-395, Apr. 2004.
    • (2004) Struct. Multidiscipl. Optim. , vol.26 , Issue.6 , pp. 369-395
    • Marler, R.T.1    Arora, J.S.2
  • 56
    • 0032348480 scopus 로고    scopus 로고
    • Normal-boundary intersection: A new method for generating Pareto optimal points in multicriteria optimization problems
    • Aug.
    • I. Das and J. E. Dennis, "Normal-boundary intersection: A new method for generating Pareto optimal points in multicriteria optimization problems," SIAM J. Optim., vol. 8, no. 3, pp. 631-657, Aug. 1998.
    • (1998) SIAM J. Optim. , vol.8 , Issue.3 , pp. 631-657
    • Das, I.1    Dennis, J.E.2
  • 57
    • 0041969992 scopus 로고    scopus 로고
    • The normalized normal constraint method for generating the Pareto frontier
    • Jul.
    • A. Messac, A. Ismail-Yahaya, and C. Mattson, "The normalized normal constraint method for generating the Pareto frontier," Struct Multidisc. Optim., vol. 25, pp. 86-98, Jul. 2003.
    • (2003) Struct Multidisc. Optim. , vol.25 , pp. 86-98
    • Messac, A.1    Ismail-Yahaya, A.2    Mattson, C.3
  • 58
    • 33745903481 scopus 로고    scopus 로고
    • Extreme learning machine: Theory and applications
    • Dec.
    • G.-B. Huang, Q.-Y. Zhu, and C.-K. Siew, "Extreme learning machine: Theory and applications," Neurocomputing, vol. 70, no. 1, pp. 489-501, Dec. 2006.
    • (2006) Neurocomputing , vol.70 , Issue.1 , pp. 489-501
    • Huang, G.-B.1    Zhu, Q.-Y.2    Siew, C.-K.3
  • 59
    • 84919642556 scopus 로고    scopus 로고
    • Is extreme learning machine feasible? A theoretical assessment (part I)
    • Jan.
    • X. Liu, S. Lin, J. Fang, and Z. Xu, "Is extreme learning machine feasible? A theoretical assessment (part I)," IEEE Trans. IEEE Trans. Neural Netw. Learn. Syst., vol. 26, no. 1, pp. 7-20, Jan. 2015.
    • (2015) IEEE Trans. IEEE Trans. Neural Netw. Learn. Syst. , vol.26 , Issue.1 , pp. 7-20
    • Liu, X.1    Lin, S.2    Fang, J.3    Xu, Z.4
  • 60
    • 84919660197 scopus 로고    scopus 로고
    • Is extreme learning machine feasible? A theoretical assessment (part II)
    • Jan.
    • S. Lin, X. Liu, J. Fang, and Z. Xu, "Is extreme learning machine feasible? A theoretical assessment (part II)," IEEE Trans. IEEE Trans. Neural Netw. Learn. Syst., vol. 26, no. 1, pp. 21-34, Jan. 2015.
    • (2015) IEEE Trans. IEEE Trans. Neural Netw. Learn. Syst. , vol.26 , Issue.1 , pp. 21-34
    • Lin, S.1    Liu, X.2    Fang, J.3    Xu, Z.4
  • 62
    • 79955702502 scopus 로고    scopus 로고
    • LIBSVM: A library for support vector machines
    • Apr. [Online]. Available:
    • C.-C. Chang and C.-J. Lin, "LIBSVM: A library for support vector machines," Trans. Intell. Syst. Technol., vol. 2, no. 3, pp. 1-39, Apr. 2001. [Online]. Available: www.csie.ntu.edu.tw/~cjlin/libsvm
    • (2001) Trans. Intell. Syst. Technol. , vol.2 , Issue.3 , pp. 1-39
    • Chang, C.-C.1    Lin, C.-J.2
  • 63
    • 84926662675 scopus 로고
    • Nearest neighbor pattern classification
    • Jan.
    • T. M. Cover and P. E. Hart, "Nearest neighbor pattern classification," IEEE Trans. Inf. Theory, vol. IT-13, no. 1, pp. 21-27, Jan. 1967.
    • (1967) IEEE Trans. Inf. Theory , vol.13 , Issue.1 , pp. 21-27
    • Cover, T.M.1    Hart, P.E.2
  • 64
    • 84867975740 scopus 로고    scopus 로고
    • A new dimensionality reduction algorithm for hyperspectral image using evolutionary strategy
    • Nov.
    • J. Yin, Y. Wang, and J. Hu, "A new dimensionality reduction algorithm for hyperspectral image using evolutionary strategy," IEEE Trans. Ind. Informat., vol. 8, no. 4, pp. 935-943, Nov. 2012.
    • (2012) IEEE Trans. Ind. Informat. , vol.8 , Issue.4 , pp. 935-943
    • Yin, J.1    Wang, Y.2    Hu, J.3


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.