World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
35
Citations
5679
World Ranking
11636
National Ranking
1438

Wei An 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 Wei An 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: 145 publications — 25th percentile

25% of scientists in this discipline score the same or lower.

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

Wei An 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 Wei An 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: 35 D-Index — 20th percentile

20% of scientists in this discipline score the same or lower.

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

Overview

Wei An is affiliated with the National University of Defense Technology in China. Their research primarily spans the fields of engineering and computer science, with a focus on subfields such as computer vision and pattern recognition, aerospace engineering, electrical and electronic engineering, media technology, and mechanics of materials.

The scientist's extensive work covers core topics including infrared target detection methodologies, advanced image processing techniques, advanced vision and imaging, remote-sensing image classification, advanced neural network applications, video surveillance and tracking methods, and advanced image and video retrieval techniques.

Wei An has collaborated frequently with several co-authors, including Yingqian Wang, Longguang Wang, Jungang Yang, Chao Xiao, and Zaiping Lin. Their publication record is distributed across prominent venues such as IEEE Transactions on Geoscience and Remote Sensing, arXiv (Cornell University), Journal of Physics Conference Series, IEEE Transactions on Pattern Analysis and Machine Intelligence, and IEEE Geoscience and Remote Sensing Letters.

Some recent papers authored by Wei An include:

  • Dense Nested Attention Network for Infrared Small Target Detection (2022, IEEE Transactions on Image Processing)
  • Infrared Dim and Small Target Detection via Multiple Subspace Learning and Spatial-Temporal Patch-Tensor Model (2020, IEEE Transactions on Geoscience and Remote Sensing)
  • Deep Video Super-Resolution Using HR Optical Flow Estimation (2020, IEEE Transactions on Image Processing)
  • MTU-Net: Multilevel TransUNet for Space-Based Infrared Tiny Ship Detection (2023, IEEE Transactions on Geoscience and Remote Sensing)
  • Deformable 3D Convolution for Video Super-Resolution (2020, IEEE Signal Processing Letters)

Best Publications

  • Dense Nested Attention Network for Infrared Small Target Detection.

    Boyang Li;Chao Xiao;Longguang Wang;Yingqian Wang

  • Unsupervised Degradation Representation Learning for Blind Super-Resolution

    Longguang Wang;Yingqian Wang;Xiaoyu Dong;Qingyu Xu

  • Exploring Sparsity in Image Super-Resolution for Efficient Inference

    Longguang Wang;Xiaoyu Dong;Yingqian Wang;Xinyi Ying

  • Learning Parallax Attention for Stereo Image Super-Resolution

    Longguang Wang;Yingqian Wang;Zhengfa Liang;Zaiping Lin

  • Infrared Dim and Small Target Detection via Multiple Subspace Learning and Spatial-Temporal Patch-Tensor Model

    Yang Sun;Jungang Yang;Wei An

  • Light Field Image Super-Resolution Using Deformable Convolution

    Yingqian Wang;Jungang Yang;Longguang Wang;Xinyi Ying

  • Spatial-Angular Interaction for Light Field Image Super-Resolution

    Yingqian Wang;Longguang Wang;Jungang Yang;Wei An

  • Learning Multi-View Representation With LSTM for 3-D Shape Recognition and Retrieval

    Chao Ma;Yulan Guo;Jungang Yang;Wei An

  • Deep Video Super-Resolution Using HR Optical Flow Estimation

    Longguang Wang;Yulan Guo;Li Liu;Zaiping Lin

  • Deformable 3D Convolution for Video Super-Resolution

    Xinyi Ying;Longguang Wang;Yingqian Wang;Weidong Sheng

  • Learning a Single Network for Scale-Arbitrary Super-Resolution

    Longguang Wang;Yingqian Wang;Zaiping Lin;Jungang Yang

  • Parallax Attention for Unsupervised Stereo Correspondence Learning.

    Longguang Wang;Yulan Guo;Yingqian Wang;Zhengfa Liang

  • Selective Light Field Refocusing for Camera Arrays Using Bokeh Rendering and Superresolution

    Yingqian Wang;Jungang Yang;Yulan Guo;Chao Xiao

  • Flickr1024: A Large-Scale Dataset for Stereo Image Super-Resolution

    Yingqian Wang;Longguang Wang;Jungang Yang;Wei An

  • Occlusion-Aware Cost Constructor for Light Field Depth Estimation

    Unknown

  • A Stereo Attention Module for Stereo Image Super-Resolution

    Xinyi Ying;Yingqian Wang;Longguang Wang;Weidong Sheng

  • Detecting and Tracking Small and Dense Moving Objects in Satellite Videos: A Benchmark

    Qian Yin;Qingyong Hu;Hao Liu;Feng Zhang

  • A Constrained Sparse Representation Model for Hyperspectral Anomaly Detection

    Qiang Ling;Yulan Guo;Zaiping Lin;Wei An

  • Symmetric Parallax Attention for Stereo Image Super-Resolution

    Yingqian Wang;Xinyi Ying;Longguang Wang;Jungang Yang

  • Learning for Video Super-Resolution through HR Optical Flow Estimation

    Longguang Wang;Yulan Guo;Zaiping Lin;Xinpu Deng

  • Non-Convex Tensor Low-Rank Approximation for Infrared Small Target Detection

    Ting Liu;Jungang Yang;Boyang Li;Chao Xiao

  • DeOccNet: Learning to See Through Foreground Occlusions in Light Fields

    Yingqian Wang;Tianhao Wu;Jungang Yang;Longguang Wang

Frequent Co-Authors

Yulan Guo
Yulan Guo Sun Yat-sen University
Jingyi Yu
Jingyi Yu ShanghaiTech University
Jonathan Li
Jonathan Li University of Waterloo

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