World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
58
Citations
25448
World Ranking
3529
National Ranking
1701

Linda G. Shapiro publication distribution in Computer Science in 2026

The chart shows the distribution of publications by all Research.com ranked scientists in the field of Computer Science in 2026. The highlighted bar marks where Linda G. Shapiro sits on this spectrum.

32–41 publications: 7 scientists 42–51 publications: 22 scientists 52–61 publications: 82 scientists 62–71 publications: 134 scientists 72–81 publications: 249 scientists 82–91 publications: 324 scientists 92–101 publications: 421 scientists 102–111 publications: 420 scientists 112–121 publications: 497 scientists 122–131 publications: 544 scientists 132–141 publications: 555 scientists 142–151 publications: 609 scientists 152–161 publications: 559 scientists 162–171 publications: 534 scientists 172–181 publications: 556 scientists 182–191 publications: 583 scientists 192–201 publications: 519 scientists 202–211 publications: 508 scientists 212–221 publications: 490 scientists 222–231 publications: 437 scientists 232–241 publications: 423 scientists 242–251 publications: 408 scientists 252–261 publications: 377 scientists 262–271 publications: 301 scientists 272–281 publications: 335 scientists 282–291 publications: 320 scientists 292–301 publications: 293 scientists 302–311 publications: 250 scientists 312–321 publications: 238 scientists 322–331 publications: 206 scientists 332–341 publications: 209 scientists 342–351 publications: 208 scientists 352–361 publications: 162 scientists 362–371 publications: 176 scientists 372–381 publications: 127 scientists 382–391 publications: 158 scientists 392–401 publications: 128 scientists 402–411 publications: 104 scientists 412–421 publications: 94 scientists 422–431 publications: 99 scientists 432–441 publications: 83 scientists 442–451 publications: 108 scientists 452–461 publications: 73 scientists 462–471 publications: 77 scientists 472–481 publications: 69 scientists 482–491 publications: 84 scientists 492–501 publications: 62 scientists 502–511 publications: 54 scientists 512–521 publications: 57 scientists 522–531 publications: 51 scientists 532–541 publications: 51 scientists 542–551 publications: 32 scientists 552–561 publications: 38 scientists 562–571 publications: 28 scientists 572–581 publications: 43 scientists 582–591 publications: 33 scientists 592–601 publications: 41 scientists 602–611 publications: 32 scientists 612–621 publications: 28 scientists 622–631 publications: 25 scientists 632–641 publications: 27 scientists 642–651 publications: 17 scientists 652–661 publications: 20 scientists 662–671 publications: 17 scientists 672–681 publications: 15 scientists 682–691 publications: 14 scientists 692–701 publications: 21 scientists 702–711 publications: 13 scientists 712–721 publications: 12 scientists 722–731 publications: 19 scientists 732–741 publications: 14 scientists 742–751 publications: 12 scientists 752–761 publications: 10 scientists 762–771 publications: 10 scientists 772–781 publications: 11 scientists 782–791 publications: 10 scientists 792–801 publications: 11 scientists 802–811 publications: 8 scientists 812–821 publications: 8 scientists 822–831 publications: 7 scientists 832–841 publications: 11 scientists 842–851 publications: 10 scientists 852–861 publications: 5 scientists 862–871 publications: 9 scientists 872–881 publications: 4 scientists 882–891 publications: 6 scientists 892–901 publications: 3 scientists 902–911 publications: 6 scientists 912–921 publications: 3 scientists 922–931 publications: 2 scientists 932–941 publications: 2 scientists 942–951 publications: 2 scientists 952–961 publications: 3 scientists 962–971 publications: 3 scientists 972–981 publications: 3 scientists 982–990 publications: 5 scientists 991+ publications: 100 scientists
32 publications 991+

This scientist: 318 publications — 77th percentile

77% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 991 publications or more.

Linda G. Shapiro D-index placement in Computer Science in 2026

The chart shows the D-index (discipline H-index) distribution of Computer Science scientists ranked by Research.com in 2026. The highlighted bar marks where Linda G. Shapiro sits on this spectrum.

30–31 D-Index: 879 scientists 32–33 D-Index: 983 scientists 34–35 D-Index: 918 scientists 36–37 D-Index: 990 scientists 38–39 D-Index: 968 scientists 40–41 D-Index: 907 scientists 42–43 D-Index: 821 scientists 44–45 D-Index: 763 scientists 46–47 D-Index: 689 scientists 48–49 D-Index: 543 scientists 50–51 D-Index: 543 scientists 52–53 D-Index: 518 scientists 54–55 D-Index: 500 scientists 56–57 D-Index: 458 scientists 58–59 D-Index: 400 scientists 60–61 D-Index: 337 scientists 62–63 D-Index: 308 scientists 64–65 D-Index: 292 scientists 66–67 D-Index: 249 scientists 68–69 D-Index: 213 scientists 70–71 D-Index: 192 scientists 72–73 D-Index: 189 scientists 74–75 D-Index: 165 scientists 76–77 D-Index: 139 scientists 78–79 D-Index: 119 scientists 80–81 D-Index: 121 scientists 82–83 D-Index: 113 scientists 84–85 D-Index: 88 scientists 86–87 D-Index: 87 scientists 88–89 D-Index: 75 scientists 90–91 D-Index: 69 scientists 92–93 D-Index: 57 scientists 94–95 D-Index: 46 scientists 96–97 D-Index: 38 scientists 98–99 D-Index: 34 scientists 100–101 D-Index: 36 scientists 102–103 D-Index: 27 scientists 104–105 D-Index: 37 scientists 106–107 D-Index: 18 scientists 108–109 D-Index: 31 scientists 110–111 D-Index: 19 scientists 112–113 D-Index: 16 scientists 114–115 D-Index: 12 scientists 116–117 D-Index: 20 scientists 118–119 D-Index: 15 scientists 120–121 D-Index: 5 scientists 122–123 D-Index: 20 scientists 124–125 D-Index: 8 scientists 126–127 D-Index: 5 scientists 128–129 D-Index: 7 scientists 130 D-Index: 3 scientists 131+ D-Index: 98 scientists
30 D-Index 131+

This scientist: 58 D-Index — 75th percentile

75% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 131 D-Index or more.

Research.com Recognitions

  • 1996 - IEEE Fellow For contributions in the theory of relational matching and its application to model-based computer vision.

Overview

Linda G. Shapiro is affiliated with the University of Washington in the United States. Their research spans the fields of computer science and medicine, with significant contributions in artificial intelligence, computer vision and pattern recognition, radiology, oncology, and genetics. The scientist's work focuses extensively on applications of AI in cancer detection, radiomics and machine learning in medical imaging, and digital imaging for blood diseases, among other topics.

Frequent coauthors collaborating with Linda G. Shapiro include Joann G. Elmore, Beibin Li, Sachin Mehta, Wenjun Wu, and Nicholas Nuechterlein.

The main publication venues for the scientist's work include:

  • arXiv (Cornell University)
  • Neuro-Oncology
  • Computerized Medical Imaging and Graphics
  • Zenodo (CERN European Organization for Nuclear Research)
  • Cardiovascular Digital Health Journal

Some recent papers authored by or involving Linda G. Shapiro are:

  • Quilt-1M: One Million Image-Text Pairs for Histopathology, 2023, PubMed
  • Artificial intelligence-enabled mobile electrocardiograms for event prediction in paroxysmal atrial fibrillation, 2023, Cardiovascular Digital Health Journal
  • End-to-End diagnosis of breast biopsy images with transformers, 2022, Medical Image Analysis
  • Machine learning techniques for mitoses classification, 2020, Computerized Medical Imaging and Graphics
  • Scale-Aware Transformers for Diagnosing Melanocytic Lesions, 2021, IEEE Access

Linda G. Shapiro has also published books, including one titled Computer Vision and Image Processing (2021) published by Springer Science+Business Media.

The scientist's main research topics covered in numerous publications are:

  • AI in cancer detection
  • Radiomics and Machine Learning in Medical Imaging
  • Digital Imaging for Blood Diseases
  • Cutaneous Melanoma Detection and Management
  • Cell Image Analysis Techniques
  • Glioma Diagnosis and Treatment
  • Colorectal Cancer Screening and Detection

Linda G. Shapiro was awarded the IEEE Fellow distinction in 1996 for contributions in the theory of relational matching and its application to model-based computer vision.

Best Publications

  • Computer and Robot Vision

    Robert M. Haralock;Linda G. Shapiro

  • Image Segmentation Techniques

    Robert M. Haralick;Linda G. Shapiro

  • ESPNet: Efficient Spatial Pyramid of Dilated Convolutions for Semantic Segmentation

    Sachin Mehta;Mohammad Rastegari;Anat Caspi;Linda G. Shapiro

  • Structural Descriptions and Inexact Matching

    Linda G. Shapiro;Robert M. Haralick

  • Morphologic edge detection

    J. Lee;R. Haralick;L. Shapiro

  • ESPNetv2: A Light-Weight, Power Efficient, and General Purpose Convolutional Neural Network

    Sachin Mehta;Mohammad Rastegari;Linda Shapiro;Hannaneh Hajishirzi

  • The Consistent Labeling Problem: Part II

    Robert M. Haralick;Linda G. Shapiro

  • A SIFT descriptor with global context

    E.N. Mortensen;Hongli Deng;L. Shapiro

  • A new connected components algorithm for virtual memory computers

    Ronald Lumia;Linda G. Shapiro;Oscar A. Zuniga

  • View-base Rendering: Visualizing Real Objects from Scanned Range and Color Data

    Kari Pulli;Michael Cohen;Tom Duchamp;Hugues Hoppe

  • A Metric for Comparing Relational Descriptions

    Linda G. Shapiro;Robert M. Haralick

  • Glossary of computer vision terms

    Robert M. Haralick;Linda G. Shapiro

  • Unsupervised Template Learning for Fine-Grained Object Recognition

    Shulin Yang;Liefeng Bo;Jue Wang;Linda G. Shapiro

  • Automated insect identification through concatenated histograms of local appearance features: feature vector generation and region detection for deformable objects

    Natalia Larios;Hongli Deng;Wei Zhang;Matt Sarpola

  • Y-Net: Joint Segmentation and Classification for Diagnosis of Breast Biopsy Images

    Sachin Mehta;Ezgi Mercan;Jamen Bartlett;Donald L. Weaver

  • Decomposition of Two-Dimensional Shapes by Graph-Theoretic Clustering

    Linda G. Shapiro;Robert M. Haralick

  • Detection and classification of cancer in whole slide breast histopathology images using deep convolutional networks.

    Baris Gecer;Selim Aksoy;Ezgi Mercan;Linda G. Shapiro

  • A Flexible Image Database System for Content-Based Retrieval

    Andrew P. Berman;Linda G. Shapiro

  • Principal Curvature-Based Region Detector for Object Recognition

    Hongli Deng;Wei Zhang;E. Mortensen;T. Dietterich

  • Modeling Stylized Character Expressions via Deep Learning

    Deepali Aneja;Alex Colburn;Gary Faigin;Linda G. Shapiro

  • Computer Vision and Image Processing

    Linda Shapiro;Azriel Rosenfeld

Frequent Co-Authors

Robert M. Haralick
Robert M. Haralick City University of New York
Joann G. Elmore
Joann G. Elmore University of California, Los Angeles
Matthew L. Speltz
Matthew L. Speltz Seattle Children's Hospital
Thomas G. Dietterich
Thomas G. Dietterich Oregon State University
David A. Lytle
David A. Lytle Oregon State University
Tad T. Brunyé
Tad T. Brunyé Tufts University
Hannaneh Hajishirzi
Hannaneh Hajishirzi University of Washington
Jenq-Neng Hwang
Jenq-Neng Hwang University of Washington
Arun K. Somani
Arun K. Somani Iowa State University

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