David A. Landgrebe - researchr alias

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Viewing Publication 1 - 48 from 48

2005

Multispectral land sensing: where from, where to?David A. Landgrebe. tgrs, 43(3):414-421, 2005. [doi]

2004

Toward an optimal supervised classifier for the analysis of hyperspectral dataMurat Dundar, David A. Landgrebe. tgrs, 42(1):271-277, 2004. [doi]

A cost-effective semisupervised classifier approach with kernelsMurat Dundar, David A. Landgrebe. tgrs, 42(1):264-270, 2004. [doi]

Nonparametric weighted feature extraction for classificationBor-Chen Kuo, David A. Landgrebe. tgrs, 42(5):1096-1105, 2004. [doi]

2003

Regularized feature extractions for hyperspectral data classificationBor-Chen Kuo, Li-Wei Ko, Chia-Hao Pai, David A. Landgrebe. igarss 2003: 1767-1769 [doi]

Gaussian mixture classifier with regularized covariance estimator for hyperspectral data classificationBor-Chen Kuo, Jinn-Min Yang, David A. Landgrebe. igarss 2003: 276-278 [doi]

Signal Theory Methods in Multispectral Remote SensingDavid A. Landgrebe. Wiley, 2003. [doi]

2002

A model-based mixture-supervised classification approach in hyperspectral data analysisMurat Dundar, David A. Landgrebe. tgrs, 40(12):2692-2699, 2002. [doi]

An adaptive method for combined covariance estimation and classificationQiong Jackson, David A. Landgrebe. tgrs, 40(5):1082-1087, 2002. [doi]

Adaptive Bayesian contextual classification based on Markov random fieldsQiong Jackson, David A. Landgrebe. tgrs, 40(11):2454-2463, 2002. [doi]

Adaptive Bayesian contextual classification based on Markov random fieldsQiong Jackson, David A. Landgrebe. igarss 2002: 1422-1424 [doi]

Hyperspectral data classification using nonparametric weighted feature extractionBor-Chen Kuo, David A. Landgrebe. igarss 2002: 1428-1430 [doi]

Regularized covariance estimators for hyperspectral data classification and its application to feature extractionBor-Chen Kuo, David A. Landgrebe. igarss 2002: 3510-3512 [doi]

A covariance estimator for small sample size classification problems and its application to feature extractionBor-Chen Kuo, David A. Landgrebe. tgrs, 40(4):814-819, 2002. [doi]

A robust classification procedure based on mixture classifiers and nonparametric weighted feature extractionBor-Chen Kuo, David A. Landgrebe. tgrs, 40(11):2486-2494, 2002. [doi]

Hyperspectral image data analysisDavid A. Landgrebe. spm, 19(1):17-28, 2002. [doi]

A process model for remote sensing data analysisVarun Madhok, David A. Landgrebe. tgrs, 40(3):680-686, 2002. [doi]

2001

An adaptive classifier design for high-dimensional data analysis with a limited training data setQiong Jackson, David A. Landgrebe. tgrs, 39(12):2664-2679, 2001. [doi]

Introduction to the special issue on analysis of hyperspectral image dataDavid A. Landgrebe, Sebastiano B. Serpico, Melba M. Crawford, Vern Singhroy. tgrs, 39(7):1343-1345, 2001. [doi]

2000

Robust parameter estimation for mixture modelSaldju Tadjudin, David A. Landgrebe. tgrs, 38(1):439-445, 2000. [doi]

1999

On the classification of classes with nearly equal spectral response in remote sensing hyperspectral image dataVictor Haertel, David A. Landgrebe. tgrs, 37(5):2374-2386, 1999. [doi]

Partially supervised classification using weighted unsupervised clusteringByeungwoo Jeon, David A. Landgrebe. tgrs, 37(2):1073-1079, 1999. [doi]

Decision fusion approach for multitemporal classificationByeungwoo Jeon, David A. Landgrebe. tgrs, 37(3):1227-1233, 1999. [doi]

Hyperspectral data analysis and supervised feature reduction via projection pursuitLuis O. Jimenez, David A. Landgrebe. tgrs, 37(6):2653-2667, 1999. [doi]

Covariance estimation with limited training samplesSaldju Tadjudin, David A. Landgrebe. tgrs, 37(4):2113-2118, 1999. [doi]

1998

Supervised classification in high-dimensional space: geometrical, statistical, and asymptotical properties of multivariate dataLuis O. Jimenez, David A. Landgrebe. tsmc, 28(1):39-54, 1998. [doi]

1997

Decision boundary feature extraction for neural networksChulhee Lee, David A. Landgrebe. tnn, 8(1):75-83, 1997. [doi]

1996

Video and image systems engineering education for the 21st centuryJan P. Allebach, Charles A. Bouman, Edward J. Coyle, Edward J. Delp, David A. Landgrebe, Anthony A. Maciejewski, Zygmunt Pizlo, Ness B. Shroff, Michael D. Zoltowski. In ICIP (1). 1996: 449-452 [doi]

Covariance Matrix Estimation and Classification With Limited Training DataJoseph P. Hoffbeck, David A. Landgrebe. pami, 18(7):763-767, 1996. [doi]

1994

Fast Parzen Density Estimation Using Clustering-Based Branch and BoundByeungwoo Jeon, David A. Landgrebe. pami, 16(9):950-954, 1994. [doi]

The effect of unlabeled samples in reducing the small sample size problem and mitigating the Hughes phenomenonBehzad M. Shahshahani, David A. Landgrebe. tgrs, 32(5):1087-1095, 1994. [doi]

1993

Feature Extraction Based on Decision BoundariesChulhee Lee, David A. Landgrebe. pami, 15(4):388-400, 1993. [doi]

Decision boundary feature extraction for nonparametric classificationChulhee Lee, David A. Landgrebe. tsmc, 23(2):433-444, 1993. [doi]

Analyzing high-dimensional multispectral dataChulhee Lee, David A. Landgrebe. tgrs, 31(4):792-800, 1993. [doi]

1992

Classification with spatio-temporal interpixel class dependency contextsByeungwoo Jeon, David A. Landgrebe. tgrs, 30(4):663-672, 1992. [doi]

1991

Parameter trade-offs for imaging spectroscopy systems [remote sensing]John P. Kerekes, David A. Landgrebe. tgrs, 29(1):57-65, 1991. [doi]

An analytical model of Earth-observational remote sensing systemsJohn P. Kerekes, David A. Landgrebe. tsmc, 21(1):125-133, 1991. [doi]

Hierarchical classifier design in high-dimensional numerous class casesByungyong Kim, David A. Landgrebe. tgrs, 29(4):518-528, 1991. [doi]

Fast likelihood classificationChulhee Lee, David A. Landgrebe. tgrs, 29(4):509-517, 1991. [doi]

An adaptive reconstruction system for spatially correlated multispectral multitemporal imagesChulhee Lee, David A. Landgrebe. tgrs, 29(4):494-508, 1991. [doi]

A survey of decision tree classifier methodologyS. Rasoul Safavian, David A. Landgrebe. tsmc, 21(3):660-674, 1991. [doi]

1989

Use of robust estimators in parametric classifiersS. Rasoul Safavian, David A. Landgrebe. SMC 1989: 356-357 [doi]

1987

Stochastic Model Utilizing Spectral and Spatial CharacteristicsH. M. Kalayeh, David A. Landgrebe. pami, 9(3):457-461, 1987. [doi]

1985

Scanning the issueDavid A. Landgrebe. pieee, 73(6):947-949, 1985. [doi]

1984

Adaptive Relaxation LabelingH. M. Kalayeh, David A. Landgrebe. pami, 6(3):369-372, 1984. [doi]

1983

Predicting the Required Number of Training SamplesH. M. Kalayeh, David A. Landgrebe. pami, 5(6):664-667, 1983. [doi]

1980

The development of a spectral-spatial classifier for earth observational dataDavid A. Landgrebe. PR, 12(3):165-175, 1980. [doi]

1976

Variance comparisons for unbiased estimators of probability of correct classification (Corresp.)David Moore, Stephen J. Whitsitt, David A. Landgrebe. TIT, 22(1):102-105, 1976. [doi]

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