World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
36
Citations
11760
World Ranking
10977
National Ranking
1356

Meng Yang 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 Meng Yang 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: 114 publications — 13th percentile

13% of scientists in this discipline score the same or lower.

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

Meng Yang 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 Meng Yang 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: 36 D-Index — 23rd percentile

23% of scientists in this discipline score the same or lower.

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

Overview

Meng Yang is affiliated with Sun Yat-sen University in China and has a research focus primarily situated in the fields of Computer Science and Engineering. Their work spans 88 publications in Computer Science and 27 in Engineering, contributing notably to various subfields and topics within these disciplines.

The main subfields of study for Meng Yang include Computer Vision and Pattern Recognition, Artificial Intelligence, Computer Networks and Communications, Electrical and Electronic Engineering, and Signal Processing. These areas reflect the scientist's broad expertise and involvement in technical aspects of computing and engineering.

The researcher's contributions emphasize several key topics, such as:

  • Domain Adaptation and Few-Shot Learning
  • Advanced Neural Network Applications
  • Video Surveillance and Tracking Methods
  • Multimodal Machine Learning Applications
  • Face and Expression Recognition
  • Topic Modeling
  • Natural Language Processing Techniques

Meng Yang has published multiple papers in prestigious venues, including:

  • "Constructing multilayer locality-constrained matrix regression framework for noise robust face super-resolution," 2020, Pattern Recognition
  • "Hierarchical Deep CNN Feature Set-Based Representation Learning for Robust Cross-Resolution Face Recognition," 2020, IEEE Transactions on Circuits and Systems for Video Technology
  • "Leaning compact and representative features for cross-modality person re-identification," 2022, World Wide Web
  • "Weakly-supervised semantic segmentation with saliency and incremental supervision updating," 2021, Pattern Recognition
  • "Deep Selective Memory Network With Selective Attention and Inter-Aspect Modeling for Aspect Level Sentiment Classification," 2021, IEEE/ACM Transactions on Audio Speech and Language Processing

The publication record also shows frequent contributions to certain venues:

  • Pattern Recognition
  • SSRN Electronic Journal
  • IEEE Transactions on Circuits and Systems for Video Technology
  • Engineering Applications of Artificial Intelligence
  • IEEE Transactions on Information Forensics and Security

Collaborative work is a significant aspect of Meng Yang's research, with frequent coauthors including Guangwei Gao, Wei-Shi Zheng, Wenfeng Luo, Yi Yu, and Jie Ling. These partnerships have resulted in multiple joint publications, reflecting a networked approach to advancing their fields of study.

Best Publications

  • Sparse representation or collaborative representation: Which helps face recognition?

    Lei Zhang;Meng Yang;Xiangchu Feng

  • Large-margin softmax loss for convolutional neural networks

    Weiyang Liu;Yandong Wen;Zhiding Yu;Meng Yang

  • Fisher Discrimination Dictionary Learning for sparse representation

    Meng Yang;Lei Zhang;Xiangchu Feng;David Zhang

  • Robust sparse coding for face recognition

    Meng Yang;Lei Zhang;Jian Yang;David Zhang

  • Gabor feature based sparse representation for face recognition with gabor occlusion dictionary

    Meng Yang;Lei Zhang

  • Sparse Representation Based Fisher Discrimination Dictionary Learning for Image Classification

    Meng Yang;Lei Zhang;Xiangchu Feng;David Zhang

  • Metaface learning for sparse representation based face recognition

    Meng Yang;Lei Zhang;Jian Yang;David Zhang

  • Toward Characteristic-Preserving Image-Based Virtual Try-On Network

    Bochao Wang;Huabin Zheng;Xiaodan Liang;Yimin Chen

  • Regularized Robust Coding for Face Recognition

    Meng Yang;Lei Zhang;Jian Yang;D. Zhang

  • Towards contactless palmprint recognition

    Lin Zhang;Lida Li;Anqi Yang;Ying Shen

  • Relaxed collaborative representation for pattern classification

    Meng Yang;Lei Zhang;David Zhang;Shenlong Wang

  • Collaborative Representation based Classification for Face Recognition

    Lei Zhang;Meng Yang;Xiangchu Feng;Yi Ma

  • Face recognition based on regularized nearest points between image sets

    Meng Yang;Pengfei Zhu;Luc Van Gool;Lei Zhang

  • Gabor feature based robust representation and classification for face recognition with Gabor occlusion dictionary

    Meng Yang;Lei Zhang;Simon C. K. Shiu;David Zhang

  • Sparse Variation Dictionary Learning for Face Recognition with a Single Training Sample per Person

    Meng Yang;Luc Van Gool;Lei Zhang

  • Joint discriminative dimensionality reduction and dictionary learning for face recognition

    Zhizhao Feng;Meng Yang;Lei Zhang;Yan Liu

  • Robust Kernel Representation With Statistical Local Features for Face Recognition

    Meng Yang;Lei Zhang;Simon Chi-Keung Shiu;D. Zhang

  • Latent Dictionary Learning for Sparse Representation Based Classification

    Meng Yang;Dengxin Dai;Lilin Shen;Luc Van Gool

  • Monogenic Binary Coding: An Efficient Local Feature Extraction Approach to Face Recognition

    Meng Yang;Lei Zhang;S. C-K Shiu;D. Zhang

  • Erasing Integrated Learning: A Simple Yet Effective Approach for Weakly Supervised Object Localization

    Jinjie Mai;Meng Yang;Wenfeng Luo

Frequent Co-Authors

Linlin Shen
Linlin Shen Shenzhen University
Lei Zhang
Lei Zhang Hong Kong Polytechnic University
David Zhang
David Zhang Chinese University of Hong Kong, Shenzhen
Jian Yang
Jian Yang University of Birmingham
Yi Yu
Yi Yu Hiroshima University
Wei-Shi Zheng
Wei-Shi Zheng Sun Yat-sen University
Pengfei Zhu
Pengfei Zhu Tianjin University
Zhihui Lai
Zhihui Lai Shenzhen University
Yuexian Zou
Yuexian Zou Peking University
Luc Van Gool
Luc Van Gool Institute for Computer Science, Artificial Intelligence and Technology (INSAIT)

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