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Feng Shao

D-Index & Metrics

Discipline name D-Index World Ranking Current World Ranking National Ranking Current National Ranking Publications Citations
Computer Science 33 12686 12317 1557 1548 241 4632

Feng Shao publications per year

The chart shows the history of publications by Feng Shao between 2005 and 2025, highlighting the no. of papers published in each year and offering an overview of the publication velocity of this scholar. Feng Shao published across 21 years, from 2005 to 2025, averaging 16.2 papers a year. Output peaked at 34 publications in 2024. 65 of the 340 publications appeared in the last two years.

No. of publications
10 20 30
Bar chart. Horizontal axis: year, 2005 to 2025. Vertical axis: number of publications, 0 to 34. Peak 34 publications in 2024. 2005: 1 publication 2006: 6 publications 2007: 4 publications 2008: 10 publications 2009: 4 publications 2010: 9 publications 2011: 14 publications 2012: 25 publications 2013: 17 publications 2014: 30 publications 2015: 19 publications 2016: 20 publications 2017: 11 publications 2018: 14 publications 2019: 13 publications 2020: 10 publications 2021: 24 publications 2022: 16 publications 2023: 28 publications 2024: 34 publications 2025: 31 publications
2005 2025

340 publications in total across all disciplines

View publications per year as a table
Feng Shao: publications per year, 2005 to 2025
Year Publications
2005 1
2006 6
2007 4
2008 10
2009 4
2010 9
2011 14
2012 25
2013 17
2014 30
2015 19
2016 20
2017 11
2018 14
2019 13
2020 10
2021 24
2022 16
2023 28
2024 34
2025 31
Total 340
Download as CSV

Feng Shao publications per year - data summary

  • Feng Shao, a Computer Science scholar from Ningbo University, has 340 publications recorded across 21 years, from 2005 to 2025.
  • The oldest publication on record dates to 2005 and the most recent to 2025.
  • The most productive year is 2024, with 34 publications.
  • The least productive year with any output is 2005, with 1 publication.
  • The rate of publication averages 16.2 papers per year over the whole span, or 16.2 per year counting only the 21 years with at least one publication.
  • The last 5 years on the chart (2021-2025) hold 133 publications, 39% of the career total.
  • Split into equal eras - 2005-2011: 48 publications (6.9 per year); 2012-2018: 136 publications (19.4 per year); 2019-2025: 156 publications (22.3 per year).
  • Comparing the opening and closing eras, the overall trend of publication is rising.

Feng Shao 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 Shao 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, 232–241 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: 241 publications — 60th percentile

60% 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
232–241 423 241
242–251 408
252–261 377
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
Download as CSV

Feng Shao publication distribution in Computer Science in 2026 - data summary

  • The chart plots the publication count of all 14,188 Computer Science scientists ranked by Research.com in 2026, grouped into 97 ranges running from 32–41 to 991+ publications.
  • Feng Shao, a Computer Science scholar from Ningbo University, records 241 publications - the 60th percentile of the discipline.
  • 60% of ranked Computer Science scientists score the same or lower than Feng Shao, and about 40% score higher.
  • The median of the discipline falls in the 202–211 publications range, and Feng Shao ranks above the median.
  • The most crowded range is 142–151 publications, holding 609 scientists (4% of the field).
  • 70% of the field sits in the lowest quarter of the value range (up to 272–281 publications), so the distribution is heavily right-skewed and high scores are rare.
  • The final bar has no upper bound: it groups every scientist with 991 publications or more, 100 scientists in all (<1% of the field).

Feng Shao 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 Shao 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, 32–33 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: 33 D-Index — 13th percentile

13% 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 33
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
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
Download as CSV

Feng Shao D-index placement in Computer Science in 2026 - data summary

  • The chart plots the discipline H-index (D-index) of all 14,188 Computer Science scientists ranked by Research.com in 2026, grouped into 52 ranges running from 30–31 to 131+ D-Index.
  • Feng Shao, a Computer Science scholar from Ningbo University, records 33 D-Index - the 13th percentile of the discipline.
  • 13% of ranked Computer Science scientists score the same or lower than Feng Shao, and about 87% score higher.
  • The median of the discipline falls in the 44–45 D-Index range, and Feng Shao ranks below the median.
  • The most crowded range is 36–37 D-Index, holding 990 scientists (7% of the field).
  • 71% of the field sits in the lowest quarter of the value range (up to 54–55 D-Index), so the distribution is heavily right-skewed and high scores are rare.
  • The final bar has no upper bound: it groups every scientist with 131 D-Index or more, 98 scientists in all (<1% of the field).

Overview

Feng Shao is a researcher affiliated with Ningbo University in China, specializing in computer science and engineering. Their work primarily focuses on areas related to computer vision and pattern recognition, with extensive contributions in media technology as well as environmental and cognitive-related fields.

The main academic fields of Feng Shao's research include:

  • Computer Science
  • Engineering

Within these broader fields, subfields of particular interest in their publications are:

  • Computer Vision and Pattern Recognition
  • Media Technology
  • Environmental Engineering
  • Cognitive Neuroscience
  • Ecology

The thematic topics they have addressed frequently in their work consist of:

  • Advanced Image Fusion Techniques
  • Visual Attention and Saliency Detection
  • Image and Video Quality Assessment
  • Image Enhancement Techniques
  • Advanced Image Processing Techniques
  • Remote-Sensing Image Classification
  • Image and Signal Denoising Methods

Feng Shao has published numerous papers in well-known venues, contributing significantly to specific journals associated with imaging and remote sensing technologies. Most frequent publication venues for their work include:

  • IEEE Transactions on Geoscience and Remote Sensing
  • IEEE Transactions on Multimedia
  • IEEE Transactions on Circuits and Systems for Video Technology
  • Journal of Visual Communication and Image Representation
  • IEEE Transactions on Instrumentation and Measurement

Among their recent scholarly papers are the following:

  • Underwater Image Enhancement Quality Evaluation: Benchmark Dataset and Objective Metric, 2022, IEEE Transactions on Circuits and Systems for Video Technology
  • A Large-Scale Benchmark Data Set for Evaluating Pansharpening Performance: Overview and Implementation, 2020, IEEE Geoscience and Remote Sensing Magazine
  • Unsupervised Decomposition and Correction Network for Low-Light Image Enhancement, 2022, IEEE Transactions on Intelligent Transportation Systems
  • Single Image Super-Resolution Quality Assessment: A Real-World Dataset, Subjective Studies, and an Objective Metric, 2022, IEEE Transactions on Image Processing
  • Vision Transformer for Pansharpening, 2022, IEEE Transactions on Geoscience and Remote Sensing

Collaboration has been a consistent element in Feng Shao's research activities. Frequent co-authors include:

  • Qiuping Jiang
  • Hangwei Chen
  • Xiangchao Meng
  • Xiongli Chai
  • Yo-Sung Ho

Best Publications

  • Underwater Image Enhancement Quality Evaluation: Benchmark Dataset and Objective Metric

    Unknown

  • Perceptual Full-Reference Quality Assessment of Stereoscopic Images by Considering Binocular Visual Characteristics

    Feng Shao;Weisi Lin;Shanbo Gu;Gangyi Jiang

  • Optimizing Multistage Discriminative Dictionaries for Blind Image Quality Assessment

    Qiuping Jiang;Feng Shao;Weisi Lin;Ke Gu

  • Unified No-Reference Quality Assessment of Singly and Multiply Distorted Stereoscopic Images

    Qiuping Jiang;Feng Shao;Wei Gao;Zhuo Chen

  • A Large-Scale Benchmark Data Set for Evaluating Pansharpening Performance: Overview and Implementation

    Xiangchao Meng;Yiming Xiong;Feng Shao;Huanfeng Shen

  • Single Image Super-Resolution Quality Assessment: A Real-World Dataset, Subjective Studies, and an Objective Metric

    Unknown

  • Unsupervised Decomposition and Correction Network for Low-Light Image Enhancement

    Unknown

  • Asymmetric Coding of Multi-View Video Plus Depth Based 3-D Video for View Rendering

    Feng Shao;Gangyi Jiang;Mei Yu;Ken Chen

  • Full-Reference Quality Assessment of Stereoscopic Images by Learning Binocular Receptive Field Properties

    Feng Shao;Kemeng Li;Weisi Lin;Gangyi Jiang

  • CGMDRNet: Cross-Guided Modality Difference Reduction Network for RGB-T Salient Object Detection

    Unknown

  • Toward a Blind Deep Quality Evaluator for Stereoscopic Images Based on Monocular and Binocular Interactions

    Feng Shao;Weijun Tian;Weisi Lin;Gangyi Jiang

  • Two-Branch Deep Neural Network for Underwater Image Enhancement in HSV Color Space

    Junkang Hu;Qiuping Jiang;Runmin Cong;Wei Gao

  • Joint Bit Allocation and Rate Control for Coding Multi-View Video Plus Depth Based 3D Video

    Feng Shao;Gangyi Jiang;Weisi Lin;Mei Yu

  • Subjective quality analyses of stereoscopic images in 3DTV system

    Junming Zhou;Gangyi Jiang;Xiangying Mao;Mei Yu

  • New fragile watermarking method for stereo image authentication with localization and recovery

    Mei Yu;Jing Wang;Gangyi Jiang;Zongju Peng

  • BLIQUE-TMI: Blind Quality Evaluator for Tone-Mapped Images Based on Local and Global Feature Analyses

    Qiuping Jiang;Feng Shao;Weisi Lin;Gangyi Jiang

  • A SAR-to-Optical Image Translation Method Based on Conditional Generation Adversarial Network (cGAN)

    Yu Li;Randi Fu;Xiangchao Meng;Wei Jin

  • Blind Image Quality Assessment for Stereoscopic Images Using Binocular Guided Quality Lookup and Visual Codebook

    Feng Shao;Weisi Lin;Shanshan Wang;Gangyi Jiang

  • Three-dimensional visual comfort assessment via preference learning

    Qiuping Jiang;Feng Shao;Gangyi Jiang;Mei Yu

  • Blind Image Quality Measurement by Exploiting High-Order Statistics With Deep Dictionary Encoding Network

    Qiuping Jiang;Wei Gao;Shiqi Wang;Guanghui Yue

  • A depth perception and visual comfort guided computational model for stereoscopic 3D visual saliency

    Qiuping Jiang;Feng Shao;Gangyi Jiang;Mei Yu

  • Difference of Gaussian statistical features based blind image quality assessment: A deep learning approach

    Yaqi Lv;Gangyi Jiang;Mei Yu;Haiyong Xu

  • No-reference Stereoscopic Image Quality Assessment Using Binocular Self-similarity and Deep Neural Network

    Yaqi Lv;Mei Yu;Gangyi Jiang;Feng Shao

  • Learning Blind Quality Evaluator for Stereoscopic Images Using Joint Sparse Representation

    Feng Shao;Kemeng Li;Weisi Lin;Gangyi Jiang

  • Learning Receptive Fields and Quality Lookups for Blind Quality Assessment of Stereoscopic Images

    Feng Shao;Weisi Lin;Shanshan Wang;Gangyi Jiang

Frequent Co-Authors

Yo-Sung Ho
Yo-Sung Ho Gwangju Institute of Science and Technology
Weisi Lin
Weisi Lin Nanyang Technological University
Qionghai Dai
Qionghai Dai Tsinghua University
Wujie Zhou
Wujie Zhou Harbin Institute of Technology
Ke Gu
Ke Gu Beijing University of Technology
Huanfeng Shen
Huanfeng Shen Wuhan University
Sam Kwong
Sam Kwong Lingnan University
Shutao Li
Shutao Li Hunan University
Shiqi Wang
Shiqi Wang City University of Hong Kong
Runmin Cong
Runmin Cong Shandong University

External Links

Personal website of Feng Shao

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