World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
34
Citations
14043
World Ranking
11875
National Ranking
4842

Yu Liu 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 Yu Liu 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: 86 publications — 5th percentile

5% of scientists in this discipline score the same or lower.

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

Yu Liu 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 Yu Liu 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: 34 D-Index — 16th percentile

16% of scientists in this discipline score the same or lower.

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

Overview

Yu Liu is affiliated with Clarkson University in the United States and has an extensive publication record primarily in the fields of engineering and medicine. Their research contributions encompass numerous subfields, including computer vision and pattern recognition, molecular biology, media technology, biomedical engineering, and electrical and electronic engineering.

The scientist's work covers a variety of topics such as advanced image fusion techniques, remote-sensing image classification, image enhancement techniques, EEG and brain-computer interfaces, gut microbiota and health, emotion and mood recognition, and heart rate variability and autonomic control.

Yu Liu has authored several recent papers, including the following:

  • Brain tumor segmentation based on the fusion of deep semantics and edge information in multimodal MRI (2022) published in Information Fusion
  • EEG-Based Emotion Recognition via Channel-Wise Attention and Self Attention (2020) published in IEEE Transactions on Affective Computing
  • DATFuse: Infrared and Visible Image Fusion via Dual Attention Transformer (2023) published in IEEE Transactions on Circuits and Systems for Video Technology
  • YDTR: Infrared and Visible Image Fusion via Y-Shape Dynamic Transformer (2022) published in IEEE Transactions on Multimedia
  • MATR: Multimodal Medical Image Fusion via Multiscale Adaptive Transformer (2022) published in IEEE Transactions on Image Processing

Frequent collaborators associated with Yu Liu's research include:

  • Xun Chen (56 publications)
  • Juan Cheng (41 publications)
  • Chang Li (29 publications)
  • Rencheng Song (23 publications)
  • Aiping Liu (10 publications)

Yu Liu's publications appear regularly in venues such as:

  • arXiv (Cornell University) with 31 publications
  • SSRN Electronic Journal with 19 publications
  • IEEE Sensors Journal with 9 publications
  • Computers in Biology and Medicine with 8 publications
  • IEEE Transactions on Instrumentation and Measurement with 8 publications

Yu Liu has also contributed to academic books, including a publication by Frontiers Media titled Multimodal Brain Image Fusion: Methods, Evaluations, and Applications released in 2023.

Best Publications

  • Deep learning in remote sensing applications: A meta-analysis and review

    Lei Ma;Yu Liu;Xueliang Zhang;Yuanxin Ye

  • A general framework for image fusion based on multi-scale transform and sparse representation

    Yu Liu;Shuping Liu;Zengfu Wang

  • IFCNN: A general image fusion framework based on convolutional neural network

    Yu Zhang;Yu Liu;Peng Sun;Han Yan

  • Multi-focus image fusion with a deep convolutional neural network

    Yu Liu;Xun Chen;Hu Peng;Zengfu Wang

  • Image Fusion With Convolutional Sparse Representation

    Yu Liu;Xun Chen;Rabab K. Ward;Z. Jane Wang

  • Deep learning for pixel-level image fusion: Recent advances and future prospects

    Yu Liu;Xun Chen;Xun Chen;Zengfu Wang;Z. Jane Wang

  • Medical Image Fusion With Parameter-Adaptive Pulse Coupled Neural Network in Nonsubsampled Shearlet Transform Domain

    Ming Yin;Xiaoning Liu;Yu Liu;Xun Chen

  • Multi-focus image fusion with dense SIFT

    Yu Liu;Shuping Liu;Zengfu Wang

  • EEG-based Emotion Recognition via Channel-wise Attention and Self Attention

    Wei Tao;Chang Li;Rencheng Song;Juan Cheng

  • Infrared and visible image fusion with convolutional neural networks

    Yu Liu;Xun Chen;Juan Cheng;Hu Peng

  • A medical image fusion method based on convolutional neural networks

    Yu Liu;Xun Chen;Juan Cheng;Hu Peng

  • Simultaneous image fusion and denoising with adaptive sparse representation

    Yu Liu;Zengfu Wang

  • Medical Image Fusion via Convolutional Sparsity Based Morphological Component Analysis

    Yu Liu;Xun Chen;Rabab K. Ward;Z. Jane Wang

  • Multi-focus image fusion: A Survey of the state of the art

    Yu Liu;Lei Wang;Juan Cheng;Chang Li

  • Emotion Recognition From Multi-Channel EEG via Deep Forest

    Juan Cheng;Meiyao Chen;Chang Li;Yu Liu

  • PulseGAN: Learning to Generate Realistic Pulse Waveforms in Remote Photoplethysmography

    Rencheng Song;Huan Chen;Juan Cheng;Chang Li

  • Video-Based Heart Rate Measurement: Recent Advances and Future Prospects

    Xun Chen;Juan Cheng;Rencheng Song;Yu Liu

  • Multi-channel EEG-based emotion recognition via a multi-level features guided capsule network.

    Yu Liu;Yufeng Ding;Chang Li;Juan Cheng

  • DeepPhos: prediction of protein phosphorylation sites with deep learning

    Fenglin Luo;Minghui Wang;Yu Liu;Xing Ming Zhao

  • Image Dehazing by an Artificial Image Fusion Method Based on Adaptive Structure Decomposition

    Mingyao Zheng;Guanqiu Qi;Zhiqin Zhu;Yuanyuan Li

  • Dense SIFT for ghost-free multi-exposure fusion

    Yu Liu;Zengfu Wang

Frequent Co-Authors

Xun Chen
Xun Chen University of Science and Technology of China
Z. Jane Wang
Z. Jane Wang University of British Columbia
Rabab K. Ward
Rabab K. Ward University of British Columbia
Xing-Ming Zhao
Xing-Ming Zhao Fudan University
Pedram Ghamisi
Pedram Ghamisi Helmholtz-Zentrum Dresden-Rossendorf
Jiayi Ma
Jiayi Ma Wuhan University
Weiming Zhang
Weiming Zhang University of Science and Technology of China
Hao Wang
Hao Wang Tianjin University
Martin J. McKeown
Martin J. McKeown University of British Columbia
Xudong Kang
Xudong Kang Hunan University

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