World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
50
Citations
11170
World Ranking
5577
National Ranking
2547

Mathematics

D-Index
49
Citations
11470
World Ranking
1134
National Ranking
518

Research.com Recognitions

  • 2013 - SIAM Fellow For contributions to matrix theory and algorithms, especially nonnegative matrices and computational methods for signal and image processing.

Overview

Robert J. Plemmons is affiliated with Wake Forest University in the United States. Their academic work primarily intersects the fields of engineering and computer science, with significant contributions to media technology and artificial intelligence. The scientist's research covers multiple subfields, including computer vision and pattern recognition, as well as ecology and analytical chemistry.

The main topics addressed in Robert J. Plemmons's work involve remote-sensing image classification, geochemistry and geologic mapping, spectroscopy and chemometric analyses, advanced image fusion techniques, image retrieval and classification techniques, remote sensing and land use, and remote sensing in agriculture.

Recent scholarly publications by Robert J. Plemmons include:

  • "Change Detection of Amazonian Alluvial Gold Mining Using Deep Learning and Sentinel-2 Imagery," 2022, Remote Sensing
  • "Superpixel-Based and Spatially Regularized Diffusion Learning for Unsupervised Hyperspectral Image Clustering," 2024, IEEE Transactions on Geoscience and Remote Sensing
  • "Unsupervised Diffusion and Volume Maximization-Based Clustering of Hyperspectral Images," 2023, Remote Sensing
  • "Classification of Hyperspectral Images Using SVM with Shape-Adaptive Reconstruction and Smoothed Total Variation," 2022, IGARSS 2022 - 2022 IEEE International Geoscience and Remote Sensing Symposium
  • "Unsupervised Detection of ASH Dieback Disease (Hymenoscyphus Fraxineus) Using Diffusion-Based Hyperspectral Image Clustering," 2022, IGARSS 2022 - 2022 IEEE International Geoscience and Remote Sensing Symposium

Frequent coauthors working alongside Robert J. Plemmons include Kangning Cui, Raymond H. Chan, Sam L. Polk, V. Paúl Pauca, and Sarra Alqahtani.

Robert J. Plemmons has contributed to publications within various venues. The most frequent publication outlets are:

  • arXiv (Cornell University)
  • IGARSS 2022 - 2022 IEEE International Geoscience and Remote Sensing Symposium
  • Remote Sensing
  • IEEE Transactions on Geoscience and Remote Sensing
  • Journal of Mathematical Imaging and Vision

Robert J. Plemmons received the SIAM Fellow award in 2013. The award citation notes their contributions to matrix theory and algorithms, specifically nonnegative matrices and computational methods for signal and image processing.

Best Publications

  • Algorithms and applications for approximate nonnegative matrix factorization

    Michael W. Berry;Murray Browne;Amy Nicole Langville;V. Paul Pauca

  • Document clustering using nonnegative matrix factorization

    Farial Shahnaz;Michael W. Berry;V.Paul Pauca;Robert J. Plemmons

  • Nonnegative matrix factorization for spectral data analysis

    V. Paul Pauca;J. Piper;Robert J. Plemmons

  • M-matrix characterizations.I—nonsingular M-matrices

    R.J. Plemmons

  • Text Mining Using Non-Negative Matrix Factorizations.

    V. Paul Pauca;Farial Shahnaz;Michael W. Berry;Robert J. Plemmons

  • Parallel algorithms for dense linear algebra computations

    K. A. Gallivan;R. J. Plemmons;A. H. Sameh

  • Nonnegativity constraints in numerical analysis.

    Donghui Chen;Robert J. Plemmons

  • Convergence of parallel multisplitting iterative methods for M-matrices

    M. Neumann;R.J. Plemmons

  • Structured low rank approximation

    Moody T. Chu;Robert E. Funderlic;Robert J. Plemmons

  • Positive diagonal solutions to the Lyapunov equations

    George Phillip Barker;Abraham Berman;Robert J. Plemmons

  • Optimality, computation, and interpretation of nonnegative matrix factorizations

    M. T. Chu;F. Diele;R. Plemmons;Stefania Ragni

  • Preconditioned iterative regularization for Ill-posed problems

    Martin Hanke;James Nagy;Robert Plemmons

  • Deblurring and Sparse Unmixing for Hyperspectral Images

    Xi-Le Zhao;Fan Wang;Ting-Zhu Huang;M. K. Ng

  • Blind deconvolution and structured matrix computations with applications to array imaging

    Kwok Po Ng;Robert J. Plemmons

  • Cones and Iterative Methods for Best Least Squares Solutions of Linear Systems

    Abraham Berman;Plemmons Robert J

  • Generalized inverses of certain Toeplitz matrices

    R.E. Cline;R.J. Plemmons;G. Worm

  • FFT-based preconditioners for Toeplitz-block least squares problems

    Raymond H. Chan;James G. Nagy;Robert J. Plemmons

  • Iterative image restoration using approximate inverse preconditioning

    J.G. Nagy;R.J. Plemmons;T.C. Torgersen

  • Least squares modifications with inverse factorizations: Parallel implications

    C.-T. Pan;R.J. Plemmons

  • Parallel Algorithms for Matrix Computations

    K. Gallivan;C. Romine;R. Plemmons;A. Sameh

Frequent Co-Authors

Abraham Berman
Abraham Berman Technion – Israel Institute of Technology
James G. Nagy
James G. Nagy Emory University
Raymond H. Chan
Raymond H. Chan Lingnan University
Michael W. Berry
Michael W. Berry University of Tennessee at Knoxville
Michael K. Ng
Michael K. Ng Hong Kong Baptist University
Michael T. Heath
Michael T. Heath University of Illinois at Urbana-Champaign
Gene H. Golub
Gene H. Golub Stanford University
Michael Neumann
Michael Neumann University of Connecticut
David J. Brady
David J. Brady University of Arizona
Moody T. Chu
Moody T. Chu North Carolina State University

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