World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
36
Citations
4899
World Ranking
11338
National Ranking
28

John See 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 John See 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: 158 publications — 30th percentile

30% of scientists in this discipline score the same or lower.

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

John See 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 John See 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: 36 D-Index — 23rd percentile

23% of scientists in this discipline score the same or lower.

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

Overview

John See is affiliated with Heriot-Watt University Malaysia in Malaysia. Their research lies primarily within the field of Computer Science, with a focus on Computer Vision and Pattern Recognition, Artificial Intelligence, Experimental and Cognitive Psychology, Aerospace Engineering, and Environmental Engineering.

Their recent publications cover a variety of topics related to advanced neural networks, video surveillance, and multimodal machine learning. Notable papers include:

  • TPM: Multiple object tracking with tracklet-plane matching, 2020, Pattern Recognition
  • AP-Loss for Accurate One-Stage Object Detection, 2020, IEEE Transactions on Pattern Analysis and Machine Intelligence
  • TA2N: Two-Stage Action Alignment Network for Few-Shot Action Recognition, 2022, Proceedings of the AAAI Conference on Artificial Intelligence
  • Dress With Style: Learning Style From Joint Deep Embedding of Clothing Styles and Body Shapes, 2020, IEEE Transactions on Multimedia
  • Towards accurate image stitching for drone-based wind turbine blade inspection, 2022, Renewable Energy

The main research themes they focus on include:

  • Human Pose and Action Recognition
  • Advanced Neural Network Applications
  • Advanced Image and Video Retrieval Techniques
  • Anomaly Detection Techniques and Applications
  • Video Surveillance and Tracking Methods
  • Multimodal Machine Learning Applications
  • Emotion and Mood Recognition

John See frequently publishes in the following venues:

  • arXiv (Cornell University)
  • Proceedings of the 30th ACM International Conference on Multimedia
  • Proceedings of the AAAI Conference on Artificial Intelligence
  • IEEE Transactions on Image Processing
  • Engineering Applications of Artificial Intelligence

Their collaborative work involves several frequent coauthors including Weiyao Lin, Huabin Liu, Yuxi Li, Cong Yang, and Ning Xu, with the highest collaboration recorded with Weiyao Lin.

John See's contributions span a substantial number of publications, with a strong specialization in algorithmic development for computer vision and pattern recognition tasks across multiple interdisciplinary areas within engineering and artificial intelligence.

Best Publications

  • Less is more: Micro-expression recognition from video using apex frame

    Sze Teng Liong;John Su Yang See;Kok Sheik Wong;Raphael Chung Wei Phan

  • LBP with Six Intersection Points: Reducing Redundant Information in LBP-TOP for Micro-expression Recognition

    Yandan Wang;John See;Raphael C.-W. Phan;Yee-Hui Oh

  • PIoU Loss: Towards Accurate Oriented Object Detection in Complex Environments

    Zhiming Chen;Kean Chen;Weiyao Lin;John See

  • Enriched Long-Term Recurrent Convolutional Network for Facial Micro-Expression Recognition

    Huai-Qian Khor;John See;Raphael Chung Wei Phan;Weiyao Lin

  • Micro-expression recognition based on 3D flow convolutional neural network

    Jing Li;Yandan Wang;John See;Wenbin Liu

  • MEGC 2019 – The Second Facial Micro-Expressions Grand Challenge

    John See;Moi Hoon Yap;Jingting Li;Xiaopeng Hong

  • Efficient Spatio-Temporal Local Binary Patterns for Spontaneous Facial Micro-Expression Recognition

    Yandan Wang;John See;Raphael C.W. Phan;Yee Hui Oh

  • A Survey of Automatic Facial Micro-Expression Analysis: Databases, Methods, and Challenges.

    Yee Hui Oh;John Su Yang See;Anh Cat Le Ngo;Raphael Chung Wei Phan

  • Dual-stream Shallow Networks for Facial Micro-expression Recognition

    Huai-Qian Khor;John See;Sze-Teng Liong;Raphael C. W. Phan

  • Towards Accurate One-Stage Object Detection With AP-Loss

    Kean Chen;Jianguo Li;Weiyao Lin;John See

  • TPM: Multiple object tracking with tracklet-plane matching

    Jinlong Peng;Tao Wang;Weiyao Lin;Jian Wang

  • Automatic apex frame spotting in micro-expression database

    Sze-Teng Liong;John See;KokSheik Wong;Anh Cat Le Ngo

  • Subtle Expression Recognition Using Optical Strain Weighted Features

    Sze-Teng Liong;John See;Raphael Chung-Wei Phan;Anh Cat Le Ngo

  • Effective recognition of facial micro-expressions with video motion magnification

    Yandan Wang;John See;Yee-Hui Oh;Raphael C.-W. Phan

  • Shallow Triple Stream Three-dimensional CNN (STSTNet) for Micro-expression Recognition

    Sze-Teng Liong;Y. S. Gan;John See;Huai-Qian Khor

  • AP-Loss for Accurate One-Stage Object Detection

    Kean Chen;Weiyao Lin;Jianguo Li;John See

  • TA2N: Two-Stage Action Alignment Network for Few-shot Action Recognition.

    Shuyuan Li;Huabin Liu;Rui Qian;Yuxi Li

  • Sparsity in Dynamics of Spontaneous Subtle Emotions: Analysis and Application

    Anh Cat Le Ngo;John See;Raphael C.-W. Phan

  • Spontaneous Subtle Expression Recognition: Imbalanced Databases and Solutions

    Anh Cat Le Ngo;Raphael Chung Wei Phan;John See

  • Spontaneous subtle expression detection and recognition based on facial strain

    Sze-Teng Liong;John See;Raphael C.-W. Phan;Yee-Hui Oh

  • Monogenic Riesz wavelet representation for micro-expression recognition

    Yee-Hui Oh;Anh Cat Le Ngo;John See;Sze-Teng Liong

  • Sparsity in Dynamics of Spontaneous Subtle Emotions: Analysis \& Application

    Anh Cat Le Ngo;John See;Raphael Chung-Wei Phan

Frequent Co-Authors

Weiyao Lin
Weiyao Lin Shanghai Jiao Tong University
Raphael C.-W. Phan
Raphael C.-W. Phan Monash University Malaysia
Wen-Huang Cheng
Wen-Huang Cheng National Yang Ming Chiao Tung University
Ling-Yu Duan
Ling-Yu Duan Peking University
Moi Hoon Yap
Moi Hoon Yap Manchester Metropolitan University
Weisi Lin
Weisi Lin Nanyang Technological University
Dietmar Saupe
Dietmar Saupe University of Konstanz
Feng Wu
Feng Wu University of Science and Technology of China
Hartwig Adam
Hartwig Adam Google (United States)
Shugong Xu
Shugong Xu Shanghai University

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