World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
39
Citations
4788
World Ranking
9900
National Ranking
1248

Yongtao Yu 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 Yongtao Yu 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: 121 publications — 15th percentile

15% of scientists in this discipline score the same or lower.

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

Yongtao Yu 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 Yongtao Yu 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: 39 D-Index — 33rd percentile

33% of scientists in this discipline score the same or lower.

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

Overview

Yongtao Yu is affiliated with the Huaiyin Institute of Technology in China. Their research primarily spans the fields of Engineering, Computer Science, and Environmental Science, with a focus on applied technology and environmental applications.

The scientist's work encompasses several subfields, including Computer Vision and Pattern Recognition, Environmental Engineering, Civil and Structural Engineering, Media Technology, and Ocean Engineering. Their main research topics concentrate on Remote Sensing and LiDAR Applications, Advanced Neural Network Applications, Remote-Sensing Image Classification, Automated Road and Building Extraction, 3D Surveying and Cultural Heritage, 3D Shape Modeling and Analysis, and Remote Sensing in Agriculture.

Yongtao Yu has published multiple papers in well-recognized venues. Some of the recent significant publications include:

  • "An attention-based multiscale transformer network for remote sensing image change detection," 2023, ISPRS Journal of Photogrammetry and Remote Sensing
  • "Land-cover classification of multispectral LiDAR data using CNN with optimized hyper-parameters," 2020, ISPRS Journal of Photogrammetry and Remote Sensing
  • "Pavement crack detection from CCD images with a locally enhanced transformer network," 2022, International Journal of Applied Earth Observation and Geoinformation
  • "Polyp Detection from Colorectum Images by Using Attentive YOLOv5," 2021, Diagnostics
  • "DA-CapsUNet: A Dual-Attention Capsule U-Net for Road Extraction from Remote Sensing Imagery," 2020, Remote Sensing

The scientist frequently publishes in venues such as the International Journal of Applied Earth Observation and Geoinformation, IEEE Geoscience and Remote Sensing Letters, Remote Sensing, IEEE Transactions on Intelligent Transportation Systems, and the ISPRS Journal of Photogrammetry and Remote Sensing.

Collaborations play a significant role in their research. Frequent co-authors include Haiyan Guan, Jonathan Li, Dilong Li, Lingfei Ma, and Changhui Yu, with co-authorship counts ranging from 8 to 33 shared publications.

Best Publications

  • Using mobile laser scanning data for automated extraction of road markings

    Haiyan Guan;Jonathan Li;Jonathan Li;Yongtao Yu;Cheng Wang

  • Use of mobile LiDAR in road information inventory: a review

    Haiyan Guan;Jonathan Li;Shuang Cao;Yongtao Yu

  • Semiautomated Extraction of Street Light Poles From Mobile LiDAR Point-Clouds

    Yongtao Yu;Jonathan Li;Haiyan Guan;Cheng Wang

  • Deep learning-based tree classification using mobile LiDAR data

    Haiyan Guan;Yongtao Yu;Zheng Ji;Jonathan Li

  • Automated Road Information Extraction From Mobile Laser Scanning Data

    Haiyan Guan;Jonathan Li;Yongtao Yu;Michael Chapman

  • Learning Hierarchical Features for Automated Extraction of Road Markings From 3-D Mobile LiDAR Point Clouds

    Yongtao Yu;Jonathan Li;Haiyan Guan;Fukai Jia

  • An attention-based multiscale transformer network for remote sensing image change detection

    Unknown

  • Multi-Scale Point-Wise Convolutional Neural Networks for 3D Object Segmentation From LiDAR Point Clouds in Large-Scale Environments

    Lingfei Ma;Ying Li;Jonathan Li;Weikai Tan

  • Extraction of power-transmission lines from vehicle-borne lidar data

    Haiyan Guan;Yongtao Yu;Jonathan Li;Zheng Ji

  • Iterative Tensor Voting for Pavement Crack Extraction Using Mobile Laser Scanning Data

    Haiyan Guan;Jonathan Li;Yongtao Yu;Michael A. Chapman

  • Bag-of-visual-phrases and hierarchical deep models for traffic sign detection and recognition in mobile laser scanning data

    Yongtao Yu;Jonathan Li;Jonathan Li;Chenglu Wen;Haiyan Guan

  • Automated Extraction of Urban Road Facilities Using Mobile Laser Scanning Data

    Yongtao Yu;Jonathan Li;Haiyan Guan;Cheng Wang

  • Land-cover classification of multispectral LiDAR data using CNN with optimized hyper-parameters

    Suoyan Pan;Haiyan Guan;Yating Chen;Yongtao Yu

  • Using Mobile LiDAR Data for Rapidly Updating Road Markings

    Haiyan Guan;Jonathan Li;Yongtao Yu;Zheng Ji

  • Rapid Localization and Extraction of Street Light Poles in Mobile LiDAR Point Clouds: A Supervoxel-Based Approach

    Fan Wu;Chenglu Wen;Yulan Guo;Jingjing Wang

  • Automated Detection of Urban Road Manhole Covers Using Mobile Laser Scanning Data

    Yongtao Yu;Haiyan Guan;Zheng Ji

  • Vehicle Detection in High-Resolution Aerial Images Based on Fast Sparse Representation Classification and Multiorder Feature

    Ziyi Chen;Cheng Wang;Huan Luo;Hanyun Wang

  • Multispectral LiDAR Point Cloud Classification Using SE-PointNet++

    Zhuangwei Jing;Haiyan Guan;Peiran Zhao;Dilong Li

  • DA-CapsUNet: A Dual-Attention Capsule U-Net for Road Extraction from Remote Sensing Imagery

    Yongfeng Ren;Yongtao Yu;Haiyan Guan

  • Robust Traffic-Sign Detection and Classification Using Mobile LiDAR Data With Digital Images

    Haiyan Guan;Wanqian Yan;Yongtao Yu;Liang Zhong

  • Semantic Labeling of Mobile LiDAR Point Clouds via Active Learning and Higher Order MRF

    Huan Luo;Cheng Wang;Chenglu Wen;Ziyi Chen

  • Spatial-Related Traffic Sign Inspection for Inventory Purposes Using Mobile Laser Scanning Data

    Chenglu Wen;Jonathan Li;Huan Luo;Yongtao Yu

Frequent Co-Authors

Haiyan Guan
Haiyan Guan Nanjing University of Information Science and Technology
Jonathan Li
Jonathan Li University of Waterloo
Cheng Wang
Cheng Wang Xiamen University
Chenglu Wen
Chenglu Wen Xiamen University
Xingjun Liu
Xingjun Liu Harbin Institute of Technology
Jun Yu
Jun Yu Hangzhou Dianzi University
Yonglong Lu
Yonglong Lu Chinese Academy of Sciences
Cheng Wang
Cheng Wang Xiamen University
Deren Li
Deren Li Wuhan University
Dawei Wang
Dawei Wang Chinese Academy of Sciences

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