World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
39
Citations
13348
World Ranking
9502
National Ranking
1203

Feng Xu 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 Feng Xu 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: 214 publications — 51st percentile

51% of scientists in this discipline score the same or lower.

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

Feng Xu 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 Feng Xu 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

Feng Xu is affiliated with Fudan University in China and has extensive research contributions in the field of engineering, particularly in aerospace engineering, biomedical engineering, computer vision and pattern recognition, electrical and electronic engineering, and environmental engineering.

Their research topics focus primarily on Synthetic Aperture Radar (SAR) applications and techniques, advanced SAR imaging techniques, microwave imaging and scattering analysis, advanced antenna and metasurface technologies, metamaterials and metasurfaces applications, geophysical methods and applications, and antenna design and analysis.

Feng Xu has published numerous papers in leading publication venues, with frequent appearances in:

  • IEEE Transactions on Geoscience and Remote Sensing
  • IEEE Transactions on Antennas and Propagation
  • IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
  • IGARSS 2022 - 2022 IEEE International Geoscience and Remote Sensing Symposium
  • IEEE Geoscience and Remote Sensing Letters

Some of their recent papers include:

  • FAIR1M: A benchmark dataset for fine-grained object recognition in high-resolution remote sensing imagery (2022), published in ISPRS Journal of Photogrammetry and Remote Sensing
  • Deep Learning Meets SAR: Concepts, models, pitfalls, and perspectives (2021), published in IEEE Geoscience and Remote Sensing Magazine
  • Tunable smart mid infrared thermal control emitter based on phase change material VO2 thin film (2023), published in Applied Thermal Engineering
  • FUSAR-Ship: building a high-resolution SAR-AIS matchup dataset of Gaofen-3 for ship detection and recognition (2020), published in Science China Information Sciences
  • Ultra long infrared metamaterial absorber with high absorption and broad band based on nano cross surrounding (2022), published in Optics & Laser Technology

Feng Xu also has a book publication titled VR/AR and 3D Displays (2021) with Springer Science+Business Media.

The scientist frequently collaborates with other researchers such as Ya-Qiu Jin, Fengming Hu, Haipeng Wang, Hecheng Jia, and Yan Wang, with multiple joint publications.

Best Publications

  • Deep Learning in Remote Sensing: A Comprehensive Review and List of Resources

    Xiao Xiang Zhu;Devis Tuia;Lichao Mou;Gui-Song Xia

  • Deep learning in remote sensing: a review

    Xiao Xiang Zhu;Devis Tuia;Lichao Mou;Gui-Song Xia

  • Target Classification Using the Deep Convolutional Networks for SAR Images

    Sizhe Chen;Haipeng Wang;Feng Xu;Ya-Qiu Jin

  • Complex-Valued Convolutional Neural Network and Its Application in Polarimetric SAR Image Classification

    Zhimian Zhang;Haipeng Wang;Feng Xu;Ya-Qiu Jin

  • FAIR1M: A Benchmark Dataset for Fine-grained Object Recognition in High-Resolution Remote Sensing Imagery

    Unknown

  • Polarimetric SAR Image Classification Using Deep Convolutional Neural Networks

    Yu Zhou;Haipeng Wang;Feng Xu;Ya-Qiu Jin

  • Deep Learning Meets SAR: Concepts, Models, Pitfalls, and Perspectives

    Xiaoxiang Zhu;Sina Montazeri;Mohsin Ali;Yuansheng Hua

  • In situ SST Quality Monitor (iQuam)

    Feng Xu;Alexander Ignatov

  • Deorientation theory of polarimetric scattering targets and application to terrain surface classification

    Feng Xu;Ya-Qiu Jin

  • Bidirectional Analytic Ray Tracing for Fast Computation of Composite Scattering From Electric-Large Target Over a Randomly Rough Surface

    Feng Xu;Ya-Qiu Jin

  • Automatic Reconstruction of Building Objects From Multiaspect Meter-Resolution SAR Images

    Feng Xu;Ya-Qiu Jin

  • Imaging Simulation of Polarimetric SAR for a Comprehensive Terrain Scene Using the Mapping and Projection Algorithm

    Feng Xu;Ya-Qiu Jin

  • Detection and Discrimination of Ship Targets in Complex Background From Spaceborne ALOS-2 SAR Images

    Wei Ao;Feng Xu;Yongchen Li;Haipeng Wang

  • Application of deep-learning algorithms to MSTAR data

    Haipeng Wang;Sizhe Chen;Feng Xu;Ya-Qiu Jin

  • A Lightweight Complex-Valued DeepLabv3+ for Semantic Segmentation of PolSAR Image

    Unknown

  • An Active Deep Learning Approach for Minimally Supervised PolSAR Image Classification

    Haixia Bi;Feng Xu;Zhiqiang Wei;Yong Xue

  • Multidimensional Feature Representation and Learning for Robust Hand-Gesture Recognition on Commercial Millimeter-Wave Radar

    Zhaoyang Xia;Yixiang Luomei;Chenglong Zhou;Feng Xu

  • Reciprocal translation between SAR and optical remote sensing images with cascaded-residual adversarial networks

    Shilei Fu;Feng Xu;Ya-Qiu Jin

  • Needles in a Haystack: Tracking City-Scale Moving Vehicles From Continuously Moving Satellite

    Wei Ao;Yanwei Fu;Xiyue Hou;Feng Xu

  • Scattering Enhanced Attention Pyramid Network for Aircraft Detection in SAR Images

    Qian Guo;Haipeng Wang;Feng Xu

  • Evaluation of in situ sea surface temperatures for use in the calibration and validation of satellite retrievals

    Feng Xu;Feng Xu;Alexander Ignatov

  • A Backscattering Model of Rainfall Over Rough Sea Surface for Synthetic Aperture Radar

    Feng Xu;Xiaofeng Li;Peng Wang;Jingsong Yang

  • 4-Bit Optimized Coding Metasurface for Wideband RCS Reduction

    Yasir Saifullah;Abu Bakar Waqas;Guo-Min Yang;Fuheng Zhang

  • Zero-Shot Learning of SAR Target Feature Space With Deep Generative Neural Networks

    Qian Song;Feng Xu

Frequent Co-Authors

Ya-Qiu Jin
Ya-Qiu Jin Fudan University
Guo-Min Yang
Guo-Min Yang Singapore Management University
Xiao Xiang Zhu
Xiao Xiang Zhu Technical University of Munich
Alejandro C. Frery
Alejandro C. Frery Victoria University of Wellington
Lichao Mou
Lichao Mou Technical University of Munich
Robert Wang
Robert Wang Chinese Academy of Sciences
Zongben Xu
Zongben Xu Xi'an Jiaotong University
Tie Jun Cui
Tie Jun Cui Southeast University
Richard Bamler
Richard Bamler German Aerospace Center
Liangpei Zhang
Liangpei Zhang Wuhan University

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