World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
36
Citations
13766
World Ranking
10966
National Ranking
1354

Tong Lu 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 Tong Lu 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: 236 publications — 58th percentile

58% of scientists in this discipline score the same or lower.

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

Tong Lu 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 Tong Lu 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

Tong Lu is affiliated with Nanjing University in China and has contributed extensively to the fields of Computer Science and Engineering. Their research primarily focuses on subfields including Computer Vision and Pattern Recognition, Artificial Intelligence, and Media Technology, with additional work in Automotive Engineering and Radiology, Nuclear Medicine and Imaging.

Their research topics cover areas such as Handwritten Text Recognition Techniques, Advanced Image and Video Retrieval Techniques, Vehicle License Plate Recognition, Multimodal Machine Learning Applications, Advanced Neural Network Applications, Human Pose and Action Recognition, and Natural Language Processing Techniques.

Among recent publications, notable papers include:

  • "Pyramid Vision Transformer: A Versatile Backbone for Dense Prediction without Convolutions," 2021, 2021 IEEE/CVF International Conference on Computer Vision (ICCV)
  • "PVT v2: Improved baselines with pyramid vision transformer," 2022, Computational Visual Media
  • "TEINet: Towards an Efficient Architecture for Video Recognition," 2020, Proceedings of the AAAI Conference on Artificial Intelligence
  • "VisionLLM: Large Language Model is also an Open-Ended Decoder for Vision-Centric Tasks," 2023, arXiv (Cornell University)
  • "PAN++: Towards Efficient and Accurate End-to-End Spotting of Arbitrarily-Shaped Text," 2021, IEEE Transactions on Pattern Analysis and Machine Intelligence

Frequent collaborators in Tong Lu's research network include:

  • Palaiahnakote Shivakumara
  • Umapada Pal
  • Michael Blumenstein
  • Wenhai Wang
  • Daniel Lopresti

Their work has been published regularly in several venues, highlighting consistent contributions to leading scientific forums. Frequent publication venues include:

  • arXiv (Cornell University)
  • Proceedings of the AAAI Conference on Artificial Intelligence
  • Pattern Recognition
  • SSRN Electronic Journal
  • International Journal of Pattern Recognition and Artificial Intelligence

Best Publications

  • Pyramid Vision Transformer: A Versatile Backbone for Dense Prediction Without Convolutions

    Wenhai Wang;Enze Xie;Xiang Li;Deng-Ping Fan

  • PVTv2: Improved Baselines with Pyramid Vision Transformer

    Wenhai Wang;Enze Xie;Xiang Li;Deng-Ping Fan

  • Shape Robust Text Detection With Progressive Scale Expansion Network

    Wenhai Wang;Enze Xie;Xiang Li;Wenbo Hou

  • Efficient and Accurate Arbitrary-Shaped Text Detection With Pixel Aggregation Network

    Wenhai Wang;Enze Xie;Xiaoge Song;Yuhang Zang

  • TEINet: Towards an Efficient Architecture for Video Recognition

    Zhaoyang Liu;Donghao Luo;Yabiao Wang;Limin Wang

  • Temporal Action Localization by Structured Maximal Sums

    Zehuan Yuan;Zehuan Yuan;Jonathan C. Stroud;Tong Lu;Jia Deng

  • PAN++: Towards Efficient and Accurate End-to-End Spotting of Arbitrarily-Shaped Text

    Wenhai Wang;Enze Xie;Xiang Li;Xuebo Liu

  • A new recognition model for electronic architectural drawings

    Tong Lu;Chiew-Lan Tai;Feng Su;Shijie Cai

  • Graphology based handwritten character analysis for human behaviour identification

    Subhankar Ghosh;Palaiahnakote Shivakumara;Prasun Roy;Umapada Pal

  • Automatic analysis and integration of architectural drawings

    Tong Lu;Huafei Yang;Ruoyu Yang;Shijie Cai

  • Riesz Fractional Based Model for Enhancing License Plate Detection and Recognition

    K. S. Raghunandan;Palaiahnakote Shivakumara;Hamid A. Jalab;Rabha W. Ibrahim

  • CNN-RNN based method for license plate recognition

    Palaiahnakote Shivakumara;Dongqi Tang;Maryam Asadzadehkaljahi;Tong Lu

  • A New Technique for Multi-Oriented Scene Text Line Detection and Tracking in Video

    Liang Wu;Palaiahnakote Shivakumara;Tong Lu;Chew Lim Tan

  • Dynamic Sampling Networks for Efficient Action Recognition in Videos

    Yin-Dong Zheng;Zhaoyang Liu;Tong Lu;Limin Wang

  • On Reinforcement Learning for Full-Length Game of StarCraft

    Zhen-Jia Pang;Ruo-Ze Liu;Zhou-Yu Meng;Yi Zhang

  • Multi-Spectral Fusion Based Approach for Arbitrarily Oriented Scene Text Detection in Video Images

    Guozhu Liang;Palaiahnakote Shivakumara;Tong Lu;Chew Lim Tan

  • TAM: Temporal Adaptive Module for Video Recognition

    Zhaoyang Liu;Limin Wang;Wayne Wu;Chen Qian

  • Multi-Script-Oriented Text Detection and Recognition in Video/Scene/Born Digital Images

    K. S. Raghunandan;Palaiahnakote Shivakumara;Sangheeta Roy;G. Hemantha Kumar

  • Deep-dense Conditional Random Fields for Object Co-segmentation

    Zehuan Yuan;Tong Lu;Yirui Wu

  • Mixed Link Networks

    Wenhai Wang;Xiang Li;Jian Yang;Tong Lu

  • Spectral 3D mesh segmentation with a novel single segmentation field

    Hao Wang;Tong Lu;Oscar Kin-Chung Au;Chiew-Lan Tai

  • Arbitrarily-Oriented Text Detection in Low Light Natural Scene Images

    Minglong Xue;Palaiahnakote Shivakumara;Chao Zhang;Yao Xiao

Frequent Co-Authors

Palaiahnakote Shivakumara
Palaiahnakote Shivakumara University of Salford
Umapada Pal
Umapada Pal Indian Statistical Institute
Chew Lim Tan
Chew Lim Tan National University of Singapore
Michael Blumenstein
Michael Blumenstein University of Technology Sydney
Wenhai Wang
Wenhai Wang Chinese University of Hong Kong
Daniel P. Lopresti
Daniel P. Lopresti Lehigh University
Enze Xie
Enze Xie Nvidia (United States)
Ping Luo
Ping Luo University of Hong Kong
Yang Yu
Yang Yu Nanjing University
Ying Tai
Ying Tai Nanjing University

If you think any of the details on this page are incorrect, let us know.

Report an issue

We appreciate your kind effort to assist us to improve this page, it would be helpful providing us with as much detail as possible in the text box below:

Related Online Degrees & Career Pathways

Studying Computer Science in the USA offers multiple pathways for advancing your career, whether you're at the start of your educational journey or looking to specialize further. Online degree programs provide flexible options to suit different backgrounds and goals.

For those seeking advanced opportunities, certain graduate degrees that are worth it in Computer Science are highly regarded by employers and can open doors to leadership roles in technology.

If you’re getting started, an associates degree online can build foundational skills and offer entry-level job prospects with the flexibility of remote study.

Cost is often a concern, but there are many options among the cheapest online colleges where you can earn a quality Computer Science degree without the heavy financial burden.

If your academic record includes a lower GPA, don’t be discouraged—there are online colleges that accept low gpa applicants, ensuring that more students have the opportunity to pursue a career in tech.

Best Scientists Citing Tong Lu

Trending Scientists

Recently Published Articles