World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
37
Citations
7955
World Ranking
10556
National Ranking
663

Hongying Meng 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 Hongying Meng 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: 186 publications — 41st percentile

41% of scientists in this discipline score the same or lower.

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

Hongying Meng 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 Hongying Meng 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: 37 D-Index — 27th percentile

27% of scientists in this discipline score the same or lower.

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

Overview

Hongying Meng is affiliated with Brunel University London in the United Kingdom. Their research spans the fields of Computer Science and Engineering, with a concentration on specific subfields such as Computer Vision and Pattern Recognition, Artificial Intelligence, Biomedical Engineering, Media Technology, and Cardiology and Cardiovascular Medicine.

Their work extensively covers topics including Video Surveillance and Tracking Methods, Human Pose and Action Recognition, Advanced Neural Network Applications, Image Processing Techniques and Applications, Advanced Vision and Imaging, Advanced Image and Video Retrieval Techniques, and Image and Signal Denoising Methods.

Meng has contributed papers to several prominent publication venues in the field. Frequent outlets for their work include Applied Sciences, SSRN Electronic Journal, IEEE Transactions on Cognitive and Developmental Systems, IEEE Transactions on Circuits and Systems for Video Technology, and arXiv (Cornell University).

Selected recent publications comprise:

  • StrongSORT: Make DeepSORT Great Again, 2023, IEEE Transactions on Multimedia
  • Medical image segmentation using deep learning: A survey, 2022, IET Image Processing
  • Automatic Modulation Recognition: A Few-Shot Learning Method Based on the Capsule Network, 2020, IEEE Wireless Communications Letters
  • Multi-region Nonuniform Brightness Correction Algorithm Based on L-Channel Gamma Transform, 2022, Security and Communication Networks
  • Robust Self-Sparse Fuzzy Clustering for Image Segmentation, 2020, IEEE Access

Meng frequently collaborates with a core group of researchers, including Ioana Crețu, Tao Lei, Alexander Tindale, Qicong Wang, and Mohammad Rafiq Swash. These collaborations have resulted in multiple joint publications and contributed to the scope of Meng's research activities.

Best Publications

  • StrongSORT: Make DeepSORT Great Again

    Unknown

  • Medical image segmentation using deep learning: A survey

    Unknown

  • The 2005 PASCAL visual object classes challenge

    Mark Everingham;Andrew Zisserman;Christopher K. I. Williams;Luc Van Gool

  • Significantly Fast and Robust Fuzzy C-Means Clustering Algorithm Based on Morphological Reconstruction and Membership Filtering

    Tao Lei;Xiaohong Jia;Yanning Zhang;Lifeng He

  • Two view learning: SVM-2K, Theory and Practice

    Jason Farquhar;David Hardoon;Hongying Meng;John S. Shawe-taylor

  • Superpixel-Based Fast Fuzzy C-Means Clustering for Color Image Segmentation

    Tao Lei;Xiaohong Jia;Yanning Zhang;Shigang Liu

  • Depression recognition based on dynamic facial and vocal expression features using partial least square regression

    Hongying Meng;Di Huang;Heng Wang;Hongyu Yang

  • What Does Touch Tell Us about Emotions in Touchscreen-Based Gameplay?

    Yuan Gao;Nadia Bianchi-Berthouze;Hongying Meng

  • Artificial Intelligent System for Automatic Depression Level Analysis Through Visual and Vocal Expressions

    Asim Jan;Hongying Meng;Yona Falinie Binti A. Gaus;Fan Zhang

  • The Automatic Detection of Chronic Pain-Related Expression: Requirements, Challenges and the Multimodal EmoPain Dataset

    Min S. H. Aung;Sebastian Kaltwang;Bernardino Romera-Paredes;Brais Martinez

  • Improving "bag-of-keypoints" image categorisation: Generative Models and PDF-Kernels

    J Farquhar;S Szedmak;H Meng;J Shawe-Taylor

  • Automatic Fuzzy Clustering Framework for Image Segmentation

    Tao Lei;Peng Liu;Xiaohong Jia;Xuande Zhang

  • A Human Action Recognition System for Embedded Computer Vision Application

    Hongying Meng;N. Pears;C. Bailey

  • Adaptive Morphological Reconstruction for Seeded Image Segmentation

    Tao Lei;Xiaohong Jia;Tongliang Liu;Shigang Liu

  • Time-Delay Neural Network for Continuous Emotional Dimension Prediction From Facial Expression Sequences

    Hongying Meng;Nadia Bianchi-Berthouze;Yangdong Deng;Jinkuang Cheng

  • Automatic Depression Scale Prediction using Facial Expression Dynamics and Regression

    Asim Jan;Hongying Meng;Yona Falinie A. Gaus;Fan Zhang

  • Affective State Level Recognition in Naturalistic Facial and Vocal Expressions

    Hongying Meng;Nadia Bianchi-Berthouze

  • Emotion detection from EEG recordings

    Jingxin Liu;Hongying Meng;Asoke Nandi;Maozhen Li

  • SMEConvNet: A Convolutional Neural Network for Spotting Spontaneous Facial Micro-Expression From Long Videos

    Zhihao Zhang;Tong Chen;Hongying Meng;Guangyuan Liu

  • Naturalistic affective expression classification by a multi-stage approach based on hidden Markov models

    Hongying Meng;Nadia Bianchi-Berthouze

  • A VLSI architecture of JPEG2000 encoder

    Leibo Liu;Ning Chen;Hongying Meng;Li Zhang

  • Medical Image Segmentation Using Deep Learning: A Survey.

    Tao Lei;Risheng Wang;Yong Wan;Xiaogang Du

Frequent Co-Authors

Asoke K. Nandi
Asoke K. Nandi Brunel University London
Nadia Bianchi-Berthouze
Nadia Bianchi-Berthouze University College London
Zhihua Wang
Zhihua Wang Tsinghua University
Leibo Liu
Leibo Liu Tsinghua University
John Shawe-Taylor
John Shawe-Taylor University College London
Michel Valstar
Michel Valstar University of Nottingham
Wojciech Mazurczyk
Wojciech Mazurczyk Warsaw University of Technology
Jian Song
Jian Song Tsinghua University
Qian Zhao
Qian Zhao Xi'an Jiaotong University
Tongliang Liu
Tongliang Liu University of Sydney

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