World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
50
Citations
11155
World Ranking
5579
National Ranking
2549

Song Wang 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 Song Wang 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: 224 publications — 55th percentile

55% of scientists in this discipline score the same or lower.

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

Song Wang 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 Song Wang 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: 50 D-Index — 62nd percentile

62% of scientists in this discipline score the same or lower.

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

Overview

Song Wang is affiliated with the University of South Carolina in the United States. Their research primarily focuses on areas within computer science and engineering, with a notable emphasis on topics such as user authentication, biometric security, and advanced signal processing techniques.

They have contributed extensively to the fields of:

  • Computer Science
  • Engineering

Their work spans several specialized subfields, including:

  • Computer Vision and Pattern Recognition
  • Information Systems
  • Signal Processing
  • Artificial Intelligence
  • Electrical and Electronic Engineering

Song Wang's main topics of academic investigation encompass:

  • User Authentication and Security Systems
  • Biometric Identification and Security
  • Advanced Steganography and Watermarking Techniques
  • EEG and Brain-Computer Interfaces
  • Neuroscience and Neural Engineering
  • Functional Brain Connectivity Studies
  • Complex Network Analysis Techniques

Their publications have appeared in various venues, frequently contributing to:

  • arXiv (Cornell University)
  • IEEE Internet of Things Journal
  • Sensors
  • Journal of Physics Conference Series
  • IEEE Open Journal of the Computer Society

Some recent papers authored or coauthored by Song Wang include:

  • "Biometrics for Internet-of-Things Security: A Review" (2021), published in Sensors
  • "A Review on Security Issues and Solutions of the Internet of Drones" (2022), published in IEEE Open Journal of the Computer Society
  • "A Review of Homomorphic Encryption for Privacy-Preserving Biometrics" (2023), published in Sensors
  • "A cancelable biometric authentication system based on feature-adaptive random projection" (2021), published in Journal of Information Security and Applications
  • "Alignment-free cancelable fingerprint templates with dual protection" (2020), published in Pattern Recognition

Song Wang collaborates frequently with several coauthors, most notably:

  • Wencheng Yang
  • Jiankun Hu
  • Xuefei Yin
  • Muhammad Shahzad
  • Jucheng Yang

Best Publications

  • CrackTree: Automatic crack detection from pavement images

    Qin Zou;Yu Cao;Qingquan Li;Qingzhou Mao

  • DeepCrack: Learning Hierarchical Convolutional Features for Crack Detection

    Qin Zou;Zheng Zhang;Qingquan Li;Xianbiao Qi

  • Learning Dynamic Siamese Network for Visual Object Tracking

    Qing Guo;Wei Feng;Ce Zhou;Rui Huang

  • Image segmentation with ratio cut

    S. Wang;J.M. Siskind

  • Visual Attention Consistency Under Image Transforms for Multi-Label Image Classification

    Hao Guo;Kang Zheng;Xiaochuan Fan;Hongkai Yu

  • Recognize Human Activities from Partially Observed Videos

    Yu Cao;Daniel Barrett;Andrei Barbu;Siddharth Narayanaswamy

  • Combining local appearance and holistic view: Dual-Source Deep Neural Networks for human pose estimation

    Xiaochuan Fan;Kang Zheng;Yuewei Lin;Song Wang

  • Effects of Image Degradation and Degradation Removal to CNN-Based Image Classification

    Yanting Pei;Yaping Huang;Qi Zou;Xingyuan Zhang

  • Salient closed boundary extraction with ratio contour

    S. Wang;T. Kubota;J.M. Siskind;J. Wang

  • Deep learning of the sectional appearances of 3D CT images for anatomical structure segmentation based on an FCN voting method.

    Xiangrong Zhou;Ryosuke Takayama;Song Wang;Takeshi Hara

  • Improved Deep Hashing With Soft Pairwise Similarity for Multi-Label Image Retrieval

    Zheng Zhang;Qin Zou;Yuewei Lin;Long Chen

  • DANNet: A One-Stage Domain Adaptation Network for Unsupervised Nighttime Semantic Segmentation

    Xinyi Wu;Zhenyao Wu;Hao Guo;Lili Ju

  • Video in sentences out

    Andrei Barbu;Alexander Bridge;Zachary Burchill;Dan Coroian

  • New benchmark for image segmentation evaluation

    Feng Ge;Song Wang;Tiecheng Liu

  • Shadow Removal by a Lightness-Guided Network With Training on Unpaired Data

    Zhihao Liu;Hui Yin;Yang Mi;Mengyang Pu

  • A Multi-Task Mean Teacher for Semi-Supervised Shadow Detection

    Zhihao Chen;Lei Zhu;Liang Wan;Song Wang

  • Auto-Exposure Fusion for Single-Image Shadow Removal

    Lan Fu;Changqing Zhou;Qing Guo;Felix Juefei-Xu

  • Dynamic Saliency-Aware Regularization for Correlation Filter-Based Object Tracking

    Wei Feng;Ruize Han;Qing Guo;Jianke Zhu

  • Domain Adaptation for Convolutional Neural Networks-Based Remote Sensing Scene Classification

    Shaoyue Song;Hongkai Yu;Zhenjiang Miao;Qiang Zhang

  • Image-Segmentation Evaluation From the Perspective of Salient Object Extraction

    Feng Ge;Song Wang;Tiecheng Liu

  • Semantic Stereo Matching With Pyramid Cost Volumes

    Zhenyao Wu;Xinyi Wu;Xiaoping Zhang;Song Wang

  • Three-Dimensional CT Image Segmentation by Combining 2D Fully Convolutional Network with 3D Majority Voting

    Xiangrong Zhou;Takaaki Ito;Ryosuke Takayama;Song Wang

  • Image segmentation with minimum mean cut

    S. Wang;J.M. Siskind

  • KinWrite: Handwriting-Based Authentication Using Kinect.

    Jing Tian;Chengzhang Qu;Wenyuan Xu;Song Wang

Frequent Co-Authors

Wei Feng
Wei Feng Tianjin University
Lili Ju
Lili Ju University of South Carolina
Yu Cao
Yu Cao University of Minnesota
Qingquan Li
Qingquan Li Shenzhen University
Hiroshi Fujita
Hiroshi Fujita Gifu University
Felix Juefei-Xu
Felix Juefei-Xu Facebook (United States)
Sven Dickinson
Sven Dickinson University of Toronto
Wenyuan Xu
Wenyuan Xu Zhejiang University
Le Lu
Le Lu Alibaba Group (China)
Zhi-Pei Liang
Zhi-Pei Liang University of Illinois at Urbana-Champaign

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