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D-Index & Metrics

Discipline name D-Index World Ranking Current World Ranking National Ranking Current National Ranking Publications Citations
Computer Science 56 4042 3928 534 531 258 13728

Kun Fu publications per year

The chart shows the history of publications by Kun Fu between 1964 and 2025, highlighting the no. of papers published in each year and offering an overview of the publication velocity of this scholar. Kun Fu published across 62 years, from 1964 to 2025, averaging 5.9 papers a year. Output peaked at 54 publications in 2021. 59 of the 363 publications appeared in the last two years.

No. of publications
10 20 30 40 50
Bar chart. Horizontal axis: year, 1964 to 2025. Vertical axis: number of publications, 0 to 54. Peak 54 publications in 2021. 1964: 1 publication 1965: 0 publications 1966: 0 publications 1967: 0 publications 1968: 0 publications 1969: 0 publications 1970: 0 publications 1971: 0 publications 1972: 0 publications 1973: 0 publications 1974: 0 publications 1975: 0 publications 1976: 0 publications 1977: 0 publications 1978: 0 publications 1979: 0 publications 1980: 0 publications 1981: 0 publications 1982: 0 publications 1983: 0 publications 1984: 1 publication 1985: 1 publication 1986: 0 publications 1987: 0 publications 1988: 0 publications 1989: 0 publications 1990: 0 publications 1991: 0 publications 1992: 0 publications 1993: 0 publications 1994: 0 publications 1995: 0 publications 1996: 0 publications 1997: 0 publications 1998: 0 publications 1999: 0 publications 2000: 0 publications 2001: 1 publication 2002: 0 publications 2003: 1 publication 2004: 1 publication 2005: 1 publication 2006: 1 publication 2007: 2 publications 2008: 1 publication 2009: 3 publications 2010: 2 publications 2011: 4 publications 2012: 3 publications 2013: 9 publications 2014: 7 publications 2015: 10 publications 2016: 13 publications 2017: 24 publications 2018: 39 publications 2019: 22 publications 2020: 25 publications 2021: 54 publications 2022: 33 publications 2023: 45 publications 2024: 28 publications 2025: 31 publications
1964 2025

363 publications in total across all disciplines

View publications per year as a table
Kun Fu: publications per year, 1964 to 2025
Year Publications
1964 1
1965 0
1966 0
1967 0
1968 0
1969 0
1970 0
1971 0
1972 0
1973 0
1974 0
1975 0
1976 0
1977 0
1978 0
1979 0
1980 0
1981 0
1982 0
1983 0
1984 1
1985 1
1986 0
1987 0
1988 0
1989 0
1990 0
1991 0
1992 0
1993 0
1994 0
1995 0
1996 0
1997 0
1998 0
1999 0
2000 0
2001 1
2002 0
2003 1
2004 1
2005 1
2006 1
2007 2
2008 1
2009 3
2010 2
2011 4
2012 3
2013 9
2014 7
2015 10
2016 13
2017 24
2018 39
2019 22
2020 25
2021 54
2022 33
2023 45
2024 28
2025 31
Total 363
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Kun Fu 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 Kun Fu sits on this spectrum.

No. of scientists
200 400 600
Bar chart with 97 bars. Horizontal axis: publications, 32–41 to 991+. Vertical axis: number of scientists, 0 to 609. Most scientists, 609, have 142–151 publications. The last bar groups every scientist with 991 publications or more. The highlighted bar, 252–261 publications, is where this scientist sits. 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
32–41 publications 991+

This scientist: 258 publications — 65th percentile

65% of scientists in this discipline score the same or lower.

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

View publications distribution as a table
Number of Computer Science scientists by publication count, Research.com 2026 ranking edition. Based on 14,188 ranked scientists.
Publications Scientists This scientist
32–41 7
42–51 22
52–61 82
62–71 134
72–81 249
82–91 324
92–101 421
102–111 420
112–121 497
122–131 544
132–141 555
142–151 609
152–161 559
162–171 534
172–181 556
182–191 583
192–201 519
202–211 508
212–221 490
222–231 437
232–241 423
242–251 408
252–261 377 258
262–271 301
272–281 335
282–291 320
292–301 293
302–311 250
312–321 238
322–331 206
332–341 209
342–351 208
352–361 162
362–371 176
372–381 127
382–391 158
392–401 128
402–411 104
412–421 94
422–431 99
432–441 83
442–451 108
452–461 73
462–471 77
472–481 69
482–491 84
492–501 62
502–511 54
512–521 57
522–531 51
532–541 51
542–551 32
552–561 38
562–571 28
572–581 43
582–591 33
592–601 41
602–611 32
612–621 28
622–631 25
632–641 27
642–651 17
652–661 20
662–671 17
672–681 15
682–691 14
692–701 21
702–711 13
712–721 12
722–731 19
732–741 14
742–751 12
752–761 10
762–771 10
772–781 11
782–791 10
792–801 11
802–811 8
812–821 8
822–831 7
832–841 11
842–851 10
852–861 5
862–871 9
872–881 4
882–891 6
892–901 3
902–911 6
912–921 3
922–931 2
932–941 2
942–951 2
952–961 3
962–971 3
972–981 3
982–990 5
991+ 100
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Kun Fu 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 Kun Fu sits on this spectrum.

No. of scientists
200 400 600 800
Bar chart with 52 bars. Horizontal axis: D-Index, 30–31 to 131+. Vertical axis: number of scientists, 0 to 990. Most scientists, 990, have 36–37 D-Index. The last bar groups every scientist with 131 D-Index or more. The highlighted bar, 56–57 D-Index, is where this scientist sits. 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
30–31 D-Index 131+

This scientist: 56 D-Index — 72nd percentile

72% of scientists in this discipline score the same or lower.

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

View D-Index distribution as a table
Number of Computer Science scientists by D-index, Research.com 2026 ranking edition. Based on 14,188 ranked scientists.
D-Index Scientists This scientist
30–31 879
32–33 983
34–35 918
36–37 990
38–39 968
40–41 907
42–43 821
44–45 763
46–47 689
48–49 543
50–51 543
52–53 518
54–55 500
56–57 458 56
58–59 400
60–61 337
62–63 308
64–65 292
66–67 249
68–69 213
70–71 192
72–73 189
74–75 165
76–77 139
78–79 119
80–81 121
82–83 113
84–85 88
86–87 87
88–89 75
90–91 69
92–93 57
94–95 46
96–97 38
98–99 34
100–101 36
102–103 27
104–105 37
106–107 18
108–109 31
110–111 19
112–113 16
114–115 12
116–117 20
118–119 15
120–121 5
122–123 20
124–125 8
126–127 5
128–129 7
130 3
131+ 98
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Overview

Kun Fu is affiliated with the University of Chinese Academy of Sciences in China. Their research spans multiple domains within computer science and engineering, focusing primarily on areas related to remote sensing and image analysis.

The scientist has contributed extensively to the fields of Computer Science and Engineering, with a significant emphasis on subfields such as Computer Vision and Pattern Recognition, Aerospace Engineering, Media Technology, Artificial Intelligence, and Civil and Structural Engineering.

Key topics covered in Kun Fu's work include:

  • Advanced Image and Video Retrieval Techniques
  • Advanced Neural Network Applications
  • Remote-Sensing Image Classification
  • Advanced SAR Imaging Techniques
  • Synthetic Aperture Radar (SAR) Applications and Techniques
  • Domain Adaptation and Few-Shot Learning
  • Remote Sensing and LiDAR Applications

Kun Fu has published papers in several prominent scientific venues, notably:

  • IEEE Transactions on Geoscience and Remote Sensing
  • IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
  • Remote Sensing
  • arXiv (Cornell University)
  • ISPRS Journal of Photogrammetry and Remote Sensing

Recent publications by Kun Fu or related closely to their research include:

  • "FAIR1M: A benchmark dataset for fine-grained object recognition in high-resolution remote sensing imagery," 2022, ISPRS Journal of Photogrammetry and Remote Sensing
  • "Rotation-aware and multi-scale convolutional neural network for object detection in remote sensing images," 2020, ISPRS Journal of Photogrammetry and Remote Sensing
  • "An Anchor-Free Method Based on Feature Balancing and Refinement Network for Multiscale Ship Detection in SAR Images," 2020, IEEE Transactions on Geoscience and Remote Sensing
  • "RingMo: A Remote Sensing Foundation Model With Masked Image Modeling," 2022, IEEE Transactions on Geoscience and Remote Sensing
  • "Research Progress on Few-Shot Learning for Remote Sensing Image Interpretation," 2021, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing

Collaborations have been frequent with several researchers, reflecting ongoing partnerships in the research community. Frequent co-authors include:

  • Xian Sun
  • Wenhui Diao
  • Hongfeng Yu
  • Yingchao Feng
  • Wenkai Zhang

Best Publications

  • SCRDet: Towards More Robust Detection for Small, Cluttered and Rotated Objects

    Xue Yang;Jirui Yang;Junchi Yan;Yue Zhang

  • Change Detection Based on Deep Siamese Convolutional Network for Optical Aerial Images

    Yang Zhan;Kun Fu;Menglong Yan;Xian Sun

  • Orientation robust object detection in aerial images using deep convolutional neural network

    Haigang Zhu;Xiaogang Chen;Weiqun Dai;Kun Fu

  • Automatic Ship Detection of Remote Sensing Images from Google Earth in Complex Scenes Based on Multi-Scale Rotation Dense Feature Pyramid Networks

    Xue Yang;Hao Sun;Kun Fu;Jirui Yang

  • A Densely Connected End-to-End Neural Network for Multiscale and Multiscene SAR Ship Detection

    Jiao Jiao;Yue Zhang;Hao Sun;Xue Yang

  • Automatic Ship Detection in Remote Sensing Images from Google Earth of Complex Scenes Based on Multiscale Rotation Dense Feature Pyramid Networks

    Xue Yang;Hao Sun;Kun Fu;Jirui Yang

  • RingMo: A Remote Sensing Foundation Model With Masked Image Modeling

    Unknown

  • FMSSD: Feature-Merged Single-Shot Detection for Multiscale Objects in Large-Scale Remote Sensing Imagery

    Peijin Wang;Xian Sun;Wenhui Diao;Kun Fu

  • SCRDet: Towards More Robust Detection for Small, Cluttered and Rotated Objects

    Xue Yang;Jirui Yang;Junchi Yan;Yue Zhang

  • Rotation-aware and multi-scale convolutional neural network for object detection in remote sensing images

    Kun Fu;Zhonghan Chang;Yue Zhang;Guangluan Xu

  • Multi-task Representation Learning for Travel Time Estimation

    Yaguang Li;Kun Fu;Zheng Wang;Cyrus Shahabi

  • An Anchor-Free Method Based on Feature Balancing and Refinement Network for Multiscale Ship Detection in SAR Images

    Jiamei Fu;Xian Sun;Zhirui Wang;Kun Fu

  • BFSIFT: A Novel Method to Find Feature Matches for SAR Image Registration

    Shanhu Wang;Hongjian You;Kun Fu

  • MARTA GANs: Unsupervised Representation Learning for Remote Sensing Image Classification

    Daoyu Lin;Kun Fu;Yang Wang;Guangluan Xu

  • Hybrid Multiple Attention Network for Semantic Segmentation in Aerial Images

    Ruigang Niu;Xian Sun;Yu Tian;Wenhui Diao

  • Efficient Saliency-Based Object Detection in Remote Sensing Images Using Deep Belief Networks

    Wenhui Diao;Xian Sun;Xinwei Zheng;Fangzheng Dou

  • Identifying Different Transportation Modes from Trajectory Data Using Tree-Based Ensemble Classifiers

    Zhibin Xiao;Yang Wang;Kun Fu;Fan Wu

  • Remote Sensing Cross-Modal Text-Image Retrieval Based on Global and Local Information

    Unknown

  • Exploring a Fine-Grained Multiscale Method for Cross-Modal Remote Sensing Image Retrieval

    Zhiqiang Yuan;Wenkai Zhang;Kun Fu;Xuan Li

  • Position Detection and Direction Prediction for Arbitrary-Oriented Ships via Multitask Rotation Region Convolutional Neural Network

    Xue Yang;Hao Sun;Xian Sun;Menglong Yan

  • A New Method on Inshore Ship Detection in High-Resolution Satellite Images Using Shape and Context Information

    Ge Liu;Yasen Zhang;Xinwei Zheng;Xian Sun

  • Object Detection in High-Resolution Remote Sensing Images Using Rotation Invariant Parts Based Model

    Wanceng Zhang;Xian Sun;Kun Fu;Chenyuan Wang

  • Automatic Water-Body Segmentation From High-Resolution Satellite Images via Deep Networks

    Ziming Miao;Kun Fu;Hao Sun;Xian Sun

Frequent Co-Authors

Xian Sun
Xian Sun University of Chinese Academy of Sciences
Wenhui Diao
Wenhui Diao Chinese Academy of Sciences
Weiya Zhang
Weiya Zhang University of Nottingham
Xue Yang
Xue Yang Shanghai Jiao Tong University
Heng-Chao Li
Heng-Chao Li Southwest Jiaotong University
William J. Emery
William J. Emery University of Colorado Boulder
Cheng Wang
Cheng Wang Xiamen University
Stefan Hinz
Stefan Hinz Karlsruhe Institute of Technology
Qixiang Ye
Qixiang Ye Chinese Academy of Sciences
Junchi Yan
Junchi Yan Shanghai Jiao Tong University

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