World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
64
Citations
14768
World Ranking
2627
National Ranking
360

Lianwen Jin 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 Lianwen Jin 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: 473 publications — 92nd percentile

92% of scientists in this discipline score the same or lower.

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

Lianwen Jin 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 Lianwen Jin 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: 64 D-Index — 82nd percentile

82% of scientists in this discipline score the same or lower.

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

Overview

Lianwen Jin is affiliated with the South China University of Technology in China. Their research primarily focuses on the field of Computer Science, with extensive work within its subfields including Computer Vision and Pattern Recognition, Artificial Intelligence, Media Technology, Human-Computer Interaction, and Signal Processing.

The scientist's work covers a range of topics, notably:

  • Handwritten Text Recognition Techniques
  • Natural Language Processing Techniques
  • Image Processing and 3D Reconstruction
  • Advanced Image and Video Retrieval Techniques
  • Image Retrieval and Classification Techniques
  • Topic Modeling
  • Vehicle License Plate Recognition

Lianwen Jin has contributed to numerous publications, with recent papers including:

  • "Decoupled Attention Network for Text Recognition," 2020, Proceedings of the AAAI Conference on Artificial Intelligence
  • "Text Recognition in the Wild," 2021, ACM Computing Surveys
  • "SwinTextSpotter: Scene Text Spotting via Better Synergy between Text Detection and Text Recognition," 2022, IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)
  • "Graph Convolutional Neural Network for Human Action Recognition: A Comprehensive Survey," 2021, IEEE Transactions on Artificial Intelligence
  • "LiLT: A Simple yet Effective Language-Independent Layout Transformer for Structured Document Understanding," 2022, Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)

Frequent collaborators include:

  • Yuliang Liu
  • Dezhi Peng
  • Canjie Luo
  • Chongyu Liu
  • Xiang Bai

Lianwen Jin's publication venues demonstrate engagement with a variety of platforms, including:

  • arXiv (Cornell University)
  • Pattern Recognition
  • Proceedings of the AAAI Conference on Artificial Intelligence
  • Journal of Image and Graphics
  • IEEE Transactions on Pattern Analysis and Machine Intelligence

Best Publications

  • MORAN: A Multi-Object Rectified Attention Network for scene text recognition

    Canjie Luo;Lianwen Jin;Zenghui Sun

  • ABCNet: Real-Time Scene Text Spotting With Adaptive Bezier-Curve Network

    Yuliang Liu;Hao Chen;Chunhua Shen;Tong He

  • Activity recognition from acceleration data based on discrete consine transform and SVM

    Zhenyu He;Lianwen Jin

  • High performance offline handwritten Chinese character recognition using GoogLeNet and directional feature maps

    Zhuoyao Zhong;Lianwen Jin;Zecheng Xie

  • Deep Matching Prior Network: Toward Tighter Multi-oriented Text Detection

    Yuliang Liu;Lianwen Jin

  • A New CNN-Based Method for Multi-Directional Car License Plate Detection

    Lele Xie;Tasweer Ahmad;Lianwen Jin;Yuliang Liu

  • Fourier Contour Embedding for Arbitrary-Shaped Text Detection

    Yiqin Zhu;Jianyong Chen;Lingyu Liang;Zhanghui Kuang

  • Decoupled Attention Network for Text Recognition

    Tianwei Wang;Yuanzhi Zhu;Lianwen Jin;Canjie Luo

  • Curved scene text detection via transverse and longitudinal sequence connection

    Yuliang Liu;Lianwen Jin;Shuaitao Zhang;Canjie Luo

  • Activity recognition from acceleration data using AR model representation and SVM

    Zhen-Yu He;Lian-Wen Jin

  • Text Recognition in the Wild: A Survey

    Xiaoxue Chen;Lianwen Jin;Yuanzhi Zhu;Canjie Luo

  • SCUT-FBP5500: A Diverse Benchmark Dataset for Multi-Paradigm Facial Beauty Prediction

    Lingyu Liang;Luojun Lin;Lianwen Jin;Duorui Xie

  • LiLT: A Simple yet Effective Language-Independent Layout Transformer for Structured Document Understanding

    Unknown

  • Person Re-Identification by Regularized Smoothing KISS Metric Learning

    Dapeng Tao;Lianwen Jin;Yongfei Wang;Yuan Yuan

  • Hierarchical Deep Reinforcement Learning for Continuous Action Control

    Zhaoyang Yang;Kathryn Merrick;Lianwen Jin;Hussein A. Abbass

  • A novel feature extraction method using Pyramid Histogram of Orientation Gradients for smile recognition

    Yang Bai;Lihua Guo;Lianwen Jin;Qinghua Huang

  • ICDAR2019 Robust Reading Challenge on Arbitrary-Shaped Text - RRC-ArT

    Chee Kheng Chng;Errui Ding;Jingtuo Liu;Dimosthenis Karatzas

  • DeepText: A new approach for text proposal generation and text detection in natural images

    Zhuoyao Zhong;Lianwen Jin;Shuangping Huang

  • Building fast and compact convolutional neural networks for offline handwritten Chinese character recognition

    Xuefeng Xiao;Lianwen Jin;Yafeng Yang;Weixin Yang

  • DropSample: A new training method to enhance deep convolutional neural networks for large-scale unconstrained handwritten Chinese character recognition

    Weixin Yang;Lianwen Jin;Dacheng Tao;Zecheng Xie

  • DeepWriterID: An End-to-End Online Text-Independent Writer Identification System

    Weixin Yang;Lianwen Jin;Manfei Liu

Frequent Co-Authors

Dapeng Tao
Dapeng Tao Yunnan University
Qinghua Huang
Qinghua Huang Northwestern Polytechnical University
Chunhua Shen
Chunhua Shen Zhejiang University
Xuelong Li
Xuelong Li China Telecom (China)
Jun Yan
Jun Yan Microsoft (United States)
Terry Lyons
Terry Lyons University of Oxford
Dacheng Tao
Dacheng Tao Nanyang Technological University
Dimosthenis Karatzas
Dimosthenis Karatzas Autonomous University of Barcelona
Errui Ding
Errui Ding Baidu (China)
Liang Lin
Liang Lin Sun Yat-sen University

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