David A. Landgrebe

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An adaptive method for combined covariance estimation and classification

Qiong Jackson, David A. Landgrebe, D. Landgrebe, 2002, IEEE Trans. Geosci. Remote. Sens..

Fast Parzen Density Estimation Using Clustering-Based Branch and Bound

David A. Landgrebe, Byeungwoo Jeon, D. Landgrebe, 1994, IEEE Trans. Pattern Anal. Mach. Intell..

David A. Landgrebe, 2005 .

On the relationship between class definition precision and classification accuracy in hyperspectral analysis

David A. Landgrebe, 2000, IGARSS 2000. IEEE 2000 International Geoscience and Remote Sensing Symposium. Taking the Pulse of the Planet: The Role of Remote Sensing in Managing the Environment. Proceedings (Cat. No.00CH37120).

The development of a spectral-spatial classifier for earth observational data

David A. Landgrebe, D. Landgrebe, 1980, Pattern Recognit..

Parameter trade-offs for imaging spectroscopy systems [remote sensing]

David A. Landgrebe, John P. Kerekes, 1991, IEEE Trans. Geosci. Remote. Sens..

The effect of unlabeled samples in reducing the small sample size problem and mitigating the Hughes phenomenon

David A. Landgrebe, Behzad M. Shahshahani, D. Landgrebe, 1994, IEEE Trans. Geosci. Remote. Sens..

An analytical model of Earth-observational remote sensing systems

David A. Landgrebe, John P. Kerekes, D. Landgrebe, 1991, IEEE Trans. Syst. Man Cybern..

Toward an optimal supervised classifier for the analysis of hyperspectral data

David A. Landgrebe, Murat Dundar, D. Landgrebe, 2004, IEEE Transactions on Geoscience and Remote Sensing.

RSSIM: A Simulation Program for Optical Remote Sensing Systems

David A. Landgrebe, John P. Kerekes, D. Landgrebe, 1989 .

Analysis Research for Earth Resource Information Systems: Where Do We Stand?

David A. Landgrebe, D. Landgrebe, 1973 .

A cost-effective semisupervised classifier approach with kernels

David A. Landgrebe, Murat Dundar, D. Landgrebe, 2004, IEEE Transactions on Geoscience and Remote Sensing.

Partially supervised classification using weighted unsupervised clustering

David A. Landgrebe, Byeungwoo Jeon, D. Landgrebe, 1999, IEEE Trans. Geosci. Remote. Sens..

A means for utilizing ancillary information in multispectral classification. [of remotely sensed data

David A. Landgrebe, John A. Richards, Philip H. Swain, 1982 .

Fast likelihood classification

David A. Landgrebe, Chulhee Lee, D. Landgrebe, 1991, IEEE Trans. Geosci. Remote. Sens..

A model-based mixture-supervised classification approach in hyperspectral data analysis

David A. Landgrebe, Murat Dundar, D. Landgrebe, 2002, IEEE Trans. Geosci. Remote. Sens..

Parameter trade-offs for imaging spectroscopy systems

David A. Landgrebe, John P. Kerekes, D. Landgrebe, 1991 .

Adaptive Bayesian contextual classification based on Markov random fields

Qiong Jackson, David A. Landgrebe, 2002, IEEE Trans. Geosci. Remote. Sens..

Boundaries in multispectral imagery by clustering

David A. Landgrebe, Arthur G. Wacker, A. G. Wacker, 1970 .

Hyperspectral Image Data Analysis as a High Dimensional Signal Processing Problem

David A. Landgrebe, D. Landgrebe, 2002 .

An Evaluation of Machine Processing Techniques of ERTS-1 Data for User Applications

David A. Landgrebe, 1973 .

Supervised classification in high-dimensional space: geometrical, statistical, and asymptotical properties of multivariate data

David A. Landgrebe, Luis O. Jimenez, D. Landgrebe, 1998, IEEE Trans. Syst. Man Cybern. Part C.

Adaptive Bayesian contextual classification based on Markov random fields

Qiong Jackson, David A. Landgrebe, D. Landgrebe, 2002, IEEE International Geoscience and Remote Sensing Symposium.

Use of unlabeled samples for mitigating the Hughes phenomenon

David A. Landgrebe, Behzad M. Shahshahani, D. Landgrebe, 1993, Proceedings of IGARSS '93 - IEEE International Geoscience and Remote Sensing Symposium.

Improved statistics estimation and feature extraction for hyperspectral data classification

Bor-Chen Kuo, David A. Landgrebe, D. Landgrebe, 2001 .

Toward a maximally effective means for analysis of hyperspectral data

David A. Landgrebe, 2002, SPIE Remote Sensing.

Information Extraction Principles and Methods for Multispectral and Hyperspectral Image Data

David A. Landgrebe, D. Landgrebe, 1999 .

Classification of remote sensing images having high spectral resolution

David A. Landgrebe, Joseph P. Hoffbeck, D. Landgrebe, 1996 .

Covariance estimation with limited training samples

David A. Landgrebe, Saldju Tadjudin, D. Landgrebe, 1999, IEEE Trans. Geosci. Remote. Sens..

A survey of decision tree classifier methodology

David A. Landgrebe, S. R. Safavian, S. Rasoul Safavian, 1991, IEEE Trans. Syst. Man Cybern..

Robust parameter estimation for mixture model

David A. Landgrebe, Saldju Tadjudin, 2000, IEEE Trans. Geosci. Remote. Sens..

Predicting the Required Number of Training Samples

David A. Landgrebe, H. M. Kalayeh, D. Landgrebe, 1983, IEEE Transactions on Pattern Analysis and Machine Intelligence.

Hierarchical classifier design in high-dimensional numerous class cases

David A. Landgrebe, Byungyong Kim, D. Landgrebe, 1991, IEEE Trans. Geosci. Remote. Sens..

Stochastic Model Utilizing Spectral and Spatial Characteristics

David A. Landgrebe, H. M. Kalayeh, D. Landgrebe, 1987, IEEE Transactions on Pattern Analysis and Machine Intelligence.

A covariance estimator for small sample size classification problems and its application to feature extraction

Bor-Chen Kuo, David A. Landgrebe, D. Landgrebe, 2002, IEEE Trans. Geosci. Remote. Sens..

Signal Theory Methods in Multispectral Remote Sensing

David A. Landgrebe, D. Landgrebe, 2003 .

An adaptive classifier design for high-dimensional data analysis with a limited training data set

Qiong Jackson, David A. Landgrebe, D. Landgrebe, 2001, IEEE Trans. Geosci. Remote. Sens..

Multispectral land sensing: where from, where to?

David A. Landgrebe, 2005, IEEE Transactions on Geoscience and Remote Sensing.

HIRIS Performance Study

David A. Landgrebe, John P. Kerekes, 1989 .

Asymptotic improvement of supervised learning by utilizing additional unlabeled samples: normal mixture density case

David A. Landgrebe, Behzad M. Shahshahani, D. Landgrebe, 1992, Optics & Photonics.

Use of robust estimators in parametric classifiers

David A. Landgrebe, S. Rasoul Safavian, 1989, Conference Proceedings., IEEE International Conference on Systems, Man and Cybernetics.

Feature Extraction Based on Decision Boundaries

David A. Landgrebe, Chulhee Lee, D. Landgrebe, 1993, IEEE Trans. Pattern Anal. Mach. Intell..

A spectral feature design system for the HIRIS/MODIS era

David A. Landgrebe, C.-C.T. Chen, 1989 .

Hyperspectral data classification using nonparametric weighted feature extraction

Bor-Chen Kuo, David A. Landgrebe, 2002, IEEE International Geoscience and Remote Sensing Symposium.

Nonparametric weighted feature extraction for classification

Bor-Chen Kuo, David A. Landgrebe, D. Landgrebe, 2004, IEEE Transactions on Geoscience and Remote Sensing.

Video and image systems engineering education for the 21st century

Zygmunt Pizlo, Jan P. Allebach, Anthony A. Maciejewski, 1996, Proceedings of 3rd IEEE International Conference on Image Processing.

Decision boundary feature extraction for nonparametric classification

David A. Landgrebe, Chulhee Lee, D. Landgrebe, 1993, IEEE Trans. Syst. Man Cybern..

Adaptive Relaxation Labeling

David A. Landgrebe, H. M. Kalayeh, 1984, IEEE Transactions on Pattern Analysis and Machine Intelligence.

A noise taxonomy for remote sensing systems

David A. Landgrebe, John P. Kerekes, 1987 .

Supplementing hyperspectral data with digital elevation

David A. Landgrebe, V. Madhok, D. Landgrebe, 1999, IEEE 1999 International Geoscience and Remote Sensing Symposium. IGARSS'99 (Cat. No.99CH36293).

Variance comparisons for unbiased estimators of probability of correct classification (Corresp.)

David A. Landgrebe, David S. Moore, Stephen J. Whitsitt, 1976, IEEE Trans. Inf. Theory.

Quantitative Use of Ancillary Data in Pixel Labeling

David A. Landgrebe, John A. Richards, Philip H. Swain, 1980 .

Statistics enhancement in hyperspectral data analysis using spectral-spatial labeling, the EM algorithm, and the leave-one-out covariance estimator

David A. Landgrebe, Pi-Fuei Hsieh, 1998, Optics & Photonics.

Analyzing high-dimensional multispectral data

David A. Landgrebe, Chulhee Lee, D. Landgrebe, 1993, IEEE Trans. Geosci. Remote. Sens..

An Analytical Approach to the Design of Spectral Measurements in the Design of Multispectral Sensor

David A. Landgrebe, Daniel J. Wiersma, 1979 .

Classification of high dimensional multispectral image data

David A. Landgrebe, Joseph P. Hoffbeck, 1993 .

Pattern Recognition in Remote Sensing

David A. Landgrebe, 2005 .

Decision fusion approach for multitemporal classification

David A. Landgrebe, Byeungwoo Jeon, D. Landgrebe, 1999, IEEE Trans. Geosci. Remote. Sens..

Introduction to the special issue on analysis of hyperspectral image data

Sebastiano B. Serpico, David A. Landgrebe, Melba M. Crawford, 2001, IEEE Trans. Geosci. Remote. Sens..

An adaptive reconstruction system for spatially correlated multispectral multitemporal images

David A. Landgrebe, Chulhee Lee, 1991, IEEE Trans. Geosci. Remote. Sens..

Simulation of optical remote sensing systems

David A. Landgrebe, John P. Kerekes, D. Landgrebe, 1989 .

A process model for remote sensing data analysis

David A. Landgrebe, Varun Madhok, 2002, IEEE Trans. Geosci. Remote. Sens..

Analytical Design of Multispectral Sensors

David A. Landgrebe, Daniel J. Wiersma, 1980, IEEE Transactions on Geoscience and Remote Sensing.

Hyperspectral data analysis and supervised feature reduction via projection pursuit

David A. Landgrebe, Luis O. Jimenez, D. Landgrebe, 1999, IEEE Trans. Geosci. Remote. Sens..

Applications of remote sensing

David A. Landgrebe, 2016 .

Decision boundary feature extraction for neural networks

David A. Landgrebe, Chulhee Lee, 1997, IEEE Trans. Neural Networks.

Regularized covariance estimators for hyperspectral data classification and its application to feature extraction

Bor-Chen Kuo, David A. Landgrebe, 2002, IEEE International Geoscience and Remote Sensing Symposium.

A robust classification procedure based on mixture classifiers and nonparametric weighted feature extraction

Bor-Chen Kuo, David A. Landgrebe, D. Landgrebe, 2002, IEEE Trans. Geosci. Remote. Sens..

High dimensional feature reduction via projection pursuit

David A. Landgrebe, L. O. Jimenez, D. Landgrebe, 1994, Proceedings of IGARSS '94 - 1994 IEEE International Geoscience and Remote Sensing Symposium.

Covariance Matrix Estimation and Classification With Limited Training Data

David A. Landgrebe, Joseph P. Hoffbeck, D. Landgrebe, 1996, IEEE Trans. Pattern Anal. Mach. Intell..

Classification of high dimensional multispectral data

David A. Landgrebe, Joseph P. Hoffbeck, D. Landgrebe, 1995 .

Progress toward information-extraction methods for hyperspectral data

David A. Landgrebe, 1997, Optics & Photonics.

Toward an optimal analysis of hyperspectral data

David A. Landgrebe, Mehmet M. Dundar, D. Landgrebe, 2003 .

Linear feature extraction for multiclass problems

David A. Landgrebe, Pi-Fuei Hsieh, 1998, IGARSS '98. Sensing and Managing the Environment. 1998 IEEE International Geoscience and Remote Sensing. Symposium Proceedings. (Cat. No.98CH36174).

DESIGN OF PARTIALLY SUPERVISED CLASSIFIERS FOR MULTISPECTRAL IMAGE DATA

Byeungwoo Jeon, David A. Landgrebe, D. Landgrebe, 1993 .

Projection pursuit in high dimensional data reduction: initial conditions, feature selection and the assumption of normality

David A. Landgrebe, L. O. Jimenez, D. Landgrebe, 1995, 1995 IEEE International Conference on Systems, Man and Cybernetics. Intelligent Systems for the 21st Century.

Spectral band selection for classification of soil organic matter content

David A. Landgrebe, M. F. Baumgardner, Tracey L. Henderson, 1989 .

Design of an Adaptive Classification Procedure for the Analysis of High-Dimensional Data with Limited Training Samples

David A. Landgrebe, Q. Jackson, D. Landgrebe, 2001 .

The relationship of sensor parameters to applications data analysis

David A. Landgrebe, E. R. Malaret, 1982 .

GEOMETRIC REGISTRATION AND CLASSIFICATION OF HYPERSPECTRAL AIRBORNE PUSHBROOM DATA

David A. Landgrebe, Chulhee Lee, James Bethel, 2000 .

Hyperspectral Data Characteristics

David A. Landgrebe, D. Landgrebe, 2005 .

On line object feature extraction for multispectral scene representation

David A. Landgrebe, Hassan Ghassemian, D. Landgrebe, 1988 .

Modeling, simulation, and analysis of optical remote sensing systems

David A. Landgrebe, John P. Kerekes, D. Landgrebe, 1989 .

Land observation sensors in perspective

David A. Landgrebe, 1983 .

Classification of multispectral data by joint supervised-unsupervised learning

David A. Landgrebe, Behzad M. Shahshahani, D. Landgrebe, 1993 .

Effect of radiance-to-reflectance transformation and atmosphere removal on maximum likelihood classification accuracy of high-dimensional remote sensing data

David A. Landgrebe, Joseph P. Hoffbeck, D. Landgrebe, 1994, Proceedings of IGARSS '94 - 1994 IEEE International Geoscience and Remote Sensing Symposium.

Lowpass filter for increasing class separability

David A. Landgrebe, Pi-Fuei Hsieh, 1998, IGARSS '98. Sensing and Managing the Environment. 1998 IEEE International Geoscience and Remote Sensing. Symposium Proceedings. (Cat. No.98CH36174).

Radiation and Sensor Systems in Remote Sensing

David A. Landgrebe, D. Landgrebe, 2005 .

An empirical study of scanner system parameters

David A. Landgrebe, Larry L. Biehl, D. Landgrebe, 1977, IEEE Transactions on Geoscience Electronics.

Proceedings of the 4th IASME/WSEAS international conference on Energy & environment

Marco Ceccarelli, Miguel A. Mariño, David A. Landgrebe, 2009 .

On Information Extraction Principles for Hyperspectral Data A White Paper

David A. Landgrebe, David A. Landgrebe, D. Landgrebe, 1997 .

Discriminant feature extraction for parametric and non-parametric classifier

David A. Landgrebe, Chia-Hoang Lee, 1992, [Proceedings] 1992 IEEE International Conference on Systems, Man, and Cybernetics.

The analytical design of spectral measurements for multispectral remote sensor systems

David A. Landgrebe, D. J. Wiersma, 1979 .

The minimum distance approach to classification

David A. Landgrebe, A. G. Wacker, D. Landgrebe, 1971 .

Covariance estimation for classifying high dimensional data

David A. Landgrebe, Joseph P. Hoffbeck, 1995, 1995 International Geoscience and Remote Sensing Symposium, IGARSS '95. Quantitative Remote Sensing for Science and Applications.

A Binary Tree Feature Selection Technique for Limited Training Sample Size

David A. Landgrebe, D. Landgrebe, M. J. Washer, 1984 .

Prediction Of Optimal Number Of Features

David A. Landgrebe, B. Kim, 1990, 10th Annual International Symposium on Geoscience and Remote Sensing.