World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
54
Citations
10811
World Ranking
4606
National Ranking
618

Bob Zhang 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 Bob Zhang 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: 296 publications — 73rd percentile

73% of scientists in this discipline score the same or lower.

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

Bob Zhang 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 Bob Zhang 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: 54 D-Index — 69th percentile

69% of scientists in this discipline score the same or lower.

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

Overview

Bob Zhang is affiliated with the University of Macau in China and has contributed extensively to the fields of computer science and engineering. Their research primarily focuses on computer vision and pattern recognition, artificial intelligence, and signal processing.

Their work covers several specific subfields including media technology and computational mechanics. Main research topics include:

  • Face and Expression Recognition
  • Biometric Identification and Security
  • Face recognition and analysis
  • Sparse and Compressive Sensing Techniques
  • Image and Signal Denoising Methods
  • Advanced Image Fusion Techniques
  • Remote-Sensing Image Classification

Bob Zhang has published a significant number of papers in leading publication venues. Frequent venues for their work include:

  • IEEE Transactions on Neural Networks and Learning Systems (11 publications)
  • arXiv (Cornell University) (11 publications)
  • IEEE Transactions on Multimedia (10 publications)
  • IEEE Transactions on Image Processing (10 publications)
  • CAAI Transactions on Intelligence Technology (9 publications)

Among the recent research papers they contributed to are:

  • Multi-stage image denoising with the wavelet transform, 2022, Pattern Recognition
  • Coarse-to-Fine CNN for Image Super-Resolution, 2020, IEEE Transactions on Multimedia
  • DRPL: Deep Regression Pair Learning for Multi-Focus Image Fusion, 2020, IEEE Transactions on Image Processing
  • Adaptive Graph Completion Based Incomplete Multi-View Clustering, 2020, IEEE Transactions on Multimedia
  • A Survey on Incomplete Multiview Clustering, 2022, IEEE Transactions on Systems Man and Cybernetics Systems

Bob Zhang frequently collaborates with several coauthors, including:

  • Lunke Fei
  • David Zhang
  • Jianhang Zhou
  • Yong Xu
  • Shuyi Li

Additionally, they have contributed to book publications, with one titled Advanced Medical Biometrics scheduled for release by World Scientific in 2025.

Best Publications

  • Retinal vessel extraction by matched filter with first-order derivative of Gaussian

    Bob Zhang;Lin Zhang;Lei Zhang;Fakhri Karray

  • Retinopathy Online Challenge: Automatic Detection of Microaneurysms in Digital Color Fundus Photographs

    Meindert Niemeijer;Bram van Ginneken;Michael J Cree;Atsushi Mizutani

  • Multi-stage image denoising with the wavelet transform

    Unknown

  • Detection of microaneurysms using multi-scale correlation coefficients

    Bob Zhang;Xiangqian Wu;Jane You;Qin Li

  • Local line directional pattern for palmprint recognition

    Yue-Tong Luo;Lan-Ying Zhao;Bob Zhang;Wei Jia

  • A Survey on Incomplete Multiview Clustering

    Unknown

  • Unified Embedding Alignment with Missing Views Inferring for Incomplete Multi-View Clustering

    Jie Wen;Zheng Zhang;Yong Xu;Bob Zhang

  • DRPL: Deep Regression Pair Learning for Multi-Focus Image Fusion

    Jinxing Li;Xiaobao Guo;Guangming Lu;Bob Zhang

  • Adaptive Graph Completion Based Incomplete Multi-View Clustering

    Jie Wen;Ke Yan;Zheng Zhang;Yong Xu

  • Coarse-to-Fine CNN for Image Super-Resolution

    Chunwei Tian;Yong Xu;Wangmeng Zuo;Bob Zhang

  • Background modeling methods in video analysis: A review and comparative evaluation

    Yong Xu;Jixiang Dong;Bob Zhang;Daoyun Xu

  • Palmprint Recognition Based on Complete Direction Representation

    Wei Jia;Bob Zhang;Jingting Lu;Yihai Zhu

  • Unified Tensor Framework for Incomplete Multi-view Clustering and Missing-view Inferring

    Jie Wen;Zheng Zhang;Zhao Zhang;Lei Zhu

  • Detecting Diabetes Mellitus and Nonproliferative Diabetic Retinopathy Using Tongue Color, Texture, and Geometry Features

    Bob Zhang;B. V. K. Vijaya Kumar;David Zhang

  • Statistical Analysis of Tongue Images for Feature Extraction and Diagnostics

    Xingzheng Wang;Bob Zhang;Zhimin Yang;Haoqian Wang

  • Linear discriminant analysis

    Unknown

  • Sparse Representation Classifier for microaneurysm detection and retinal blood vessel extraction

    Bob Zhang;Fakhri Karray;Qin Li;Lei Zhang

  • Adaptive weighted nonnegative low-rank representation

    Jie Wen;Bob Zhang;Yong Xu;Jian Yang

  • CDIMC-net: Cognitive Deep Incomplete Multi-view Clustering Network

    Jie Wen;Zheng Zhang;Yong Xu;Bob Zhang

  • Learning Discriminant Direction Binary Palmprint Descriptor

    Lunke Fei;Bob Zhang;Yong Xu;Zhenhua Guo

  • Class-Specific Reconstruction Transfer Learning for Visual Recognition Across Domains

    Shanshan Wang;Lei Zhang;Wangmeng Zuo;Bob Zhang

  • Multiple representations and sparse representation for image classification

    Yong Xu;Bob Zhang;Zuofeng Zhong

  • Sample diversity, representation effectiveness and robust dictionary learning for face recognition

    Yong Xu;Zhengming Li;Bob Zhang;Jian Yang

Frequent Co-Authors

David Zhang
David Zhang Chinese University of Hong Kong, Shenzhen
Yong Xu
Yong Xu Harbin Institute of Technology
Lunke Fei
Lunke Fei Guangdong University of Technology
Jane You
Jane You Hong Kong Polytechnic University
Fakhri Karray
Fakhri Karray Mohamed bin Zayed University of Artificial Intelligence
Yuan Yan Tang
Yuan Yan Tang University of Macau
Jian Yang
Jian Yang University of Birmingham
Lei Zhang
Lei Zhang Hong Kong Polytechnic University
Meng Yang
Meng Yang Sun Yat-sen University
Wangmeng Zuo
Wangmeng Zuo Harbin Institute of Technology

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