World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
56
Citations
20784
World Ranking
3960
National Ranking
1882

Research.com Recognitions

  • 1999 - Fellow of the American Association for the Advancement of Science (AAAS)

Overview

David A. Landgrebe is affiliated with Purdue University West Lafayette in the United States. Their research contributions include work on agricultural systems and expert systems applied to improve prediction accuracy and the resolution of scenarios within agriculture.

Recent publications by Landgrebe include the paper titled "Expert system approach to improve the accuracy of prediction and solution of various agricultural scenarios", published in 2023 in the journal Idea Future Research.

  • Expert system approach to improve the accuracy of prediction and solution of various agricultural scenarios (2023, Idea Future Research)

Frequent coauthors collaborating with Landgrebe are:

  • Tambun Sihotang
  • Firta Sari Panjaitan

Landgrebe has published in the venue Idea Future Research.

  • Idea Future Research

Among accolades, Landgrebe was named a Fellow of the American Association for the Advancement of Science (AAAS) in 1999.

Best Publications

  • A survey of decision tree classifier methodology

    S.R. Safavian;D. Landgrebe

  • Hyperspectral image data analysis

    D. Landgrebe

  • Remote sensing: The quantitative approach

    S. M. Davis;D. A. Landgrebe;T. L. Phillips;P. H. Swain

  • Signal Theory Methods in Multispectral Remote Sensing

    David A. Landgrebe

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

    B.M. Shahshahani;D.A. Landgrebe

  • Classification of Multispectral Image Data by Extraction and Classification of Homogeneous Objects

    R. L. Kettig;D. A. Landgrebe

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

    L.O. Jimenez;D.A. Landgrebe

  • Nonparametric weighted feature extraction for classification

    Bor-Chen Kuo;D.A. Landgrebe

  • Feature extraction based on decision boundaries

    C. Lee;D.A. Landgrebe

  • Covariance matrix estimation and classification with limited training data

    J.P. Hoffbeck;D.A. Landgrebe

  • Hyperspectral data analysis and supervised feature reduction via projection pursuit

    L.O. Jimenez;D.A. Landgrebe

  • 220 Band AVIRIS Hyperspectral Image Data Set: June 12, 1992 Indian Pine Test Site 3

    Marion F. Baumgardner;Larry L. Biehl;David A. Landgrebe

  • Adaptive Bayesian contextual classification based on Markov random fields

    Q. Jackson;D.A. Landgrebe

  • Analyzing high-dimensional multispectral data

    Chulhee Lee;D. A. Landgrebe

  • Covariance estimation with limited training samples

    S. Tadjudin;D.A. Landgrebe

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

    Q. Jackson;D.A. Landgrebe

  • Information Extraction Principles and Methods for Multispectral and Hyperspectral Image Data

    David Landgrebe

  • Decision boundary feature extraction for neural networks

    Chulhee Lee;D.A. Landgrebe

  • Decision fusion approach for multitemporal classification

    Byeungwoo Jeon;D.A. Landgrebe

  • MultiSpec: a tool for multispectral--hyperspectral image data analysis

    Larry Biehl;David Landgrebe

Frequent Co-Authors

Leonid Perlovsky
Leonid Perlovsky Northeastern University
Hassan Ghassemian
Hassan Ghassemian Tarbiat Modares University
Dionysios D. Dionysiou
Dionysios D. Dionysiou University of Cincinnati
Jon Atli Benediktsson
Jon Atli Benediktsson University of Iceland
Bernard A. Engel
Bernard A. Engel Purdue University West Lafayette
Sebastiano B. Serpico
Sebastiano B. Serpico University of Genoa
Li-Wei Ko
Li-Wei Ko National Yang Ming Chiao Tung University

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