World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
62
Citations
15950
World Ranking
2891
National Ranking
396

Meng Joo Er 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 Meng Joo Er 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: 440 publications — 90th percentile

90% of scientists in this discipline score the same or lower.

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

Meng Joo Er 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 Meng Joo Er 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: 62 D-Index — 80th percentile

80% of scientists in this discipline score the same or lower.

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

Overview

Meng Joo Er is affiliated with Dalian Maritime University in China, specializing in research at the intersection of engineering and computer science. Their work primarily encompasses control and systems engineering, computer vision and pattern recognition, and ocean engineering, reflecting an interdisciplinary approach to maritime technology and intelligent control systems.

The scientist's research focuses on several specialized subfields, including:

  • Control and Systems Engineering
  • Computer Vision and Pattern Recognition
  • Ocean Engineering
  • Computer Networks and Communications
  • Aerospace Engineering

The main topics addressed in their publications highlight expertise in adaptive control techniques and autonomous maritime systems:

  • Adaptive Control of Nonlinear Systems
  • Underwater Vehicles and Communication Systems
  • Advanced Neural Network Applications
  • Distributed Control Multi-Agent Systems
  • Maritime Navigation and Safety
  • Robotic Path Planning Algorithms
  • Adaptive Dynamic Programming Control

Frequent coauthors collaborating with Meng Joo Er include:

  • Yi Liu
  • Huibin Gong
  • Jie Chen
  • Qiong Chang
  • Chuang Ma

Publications by Meng Joo Er are often disseminated through notable venues with significant contributions in the fields of ocean engineering and intelligent systems. Regular publication venues include:

  • Ocean Engineering
  • IEEE Transactions on Systems Man and Cybernetics Systems
  • 2021 6th International Conference on Automation, Control and Robotics Engineering (CACRE)
  • Artificial Intelligence Review
  • IEEE/ASME Transactions on Mechatronics

Some recent papers authored by Meng Joo Er demonstrate a focus on marine object recognition, autonomous surface vehicles, and ship detection leveraging deep learning and intelligent control methodologies:

  • Intelligent motion control of unmanned surface vehicles: A critical review, 2023, Ocean Engineering
  • Ship detection with deep learning: a survey, 2023, Artificial Intelligence Review
  • Review on deep learning techniques for marine object recognition: Architectures and algorithms, 2020, Control Engineering Practice

These publications reflect ongoing efforts to integrate advanced neural networks, adaptive control, and multi-agent distributed control mechanisms within maritime and robotic applications. Meng Joo Er's work contributes to developing systems for enhanced navigation, autonomous vessel operation, and underwater communication under complex environmental conditions.

Best Publications

  • A review of clustering techniques and developments

    Amit Saxena;Mukesh Prasad;Akshansh Gupta;Neha Bharill

  • Face recognition with radial basis function (RBF) neural networks

    Meng Joo Er;Shiqian Wu;Juwei Lu;Hock Lye Toh

  • Illumination compensation and normalization for robust face recognition using discrete cosine transform in logarithm domain

    W. Chen;Meng Joo Er;Shiqian Wu

  • Dynamic fuzzy neural networks-a novel approach to function approximation

    Shiqian Wu;Meng Joo Er

  • A fast approach for automatic generation of fuzzy rules by generalized dynamic fuzzy neural networks

    Shiqian Wu;Meng Joo Er;Yang Gao

  • High-speed face recognition based on discrete cosine transform and RBF neural networks

    Meng Joo Er;W. Chen;Shiqian Wu

  • NARMAX time series model prediction: feedforward and recurrent fuzzy neural network approaches

    Yang Gao;Meng Joo Er

  • Wireless Sensor Networks for Industrial Environments

    K.S. Low;W.N.N. Win;M.J. Er

  • Online adaptive fuzzy neural identification and control of a class of MIMO nonlinear systems

    Yang Gao;Meng Joo Er

  • Coverage path planning for UAVs based on enhanced exact cellular decomposition method

    Yan Li;Hai Chen;Meng Joo Er;Xinmin Wang

  • A hybrid particle swarm optimization based fuzzy expert system for the diagnosis of coronary artery disease

    S. Muthukaruppan;M. J. Er

  • Direct Adaptive Fuzzy Tracking Control of Marine Vehicles With Fully Unknown Parametric Dynamics and Uncertainties

    Ning Wang;Meng Joo Er

  • Adaptive Robust Online Constructive Fuzzy Control of a Complex Surface Vehicle System

    Ning Wang;Meng Joo Er;Jing-Chao Sun;Yan-Cheng Liu

  • Online tuning of fuzzy inference systems using dynamic fuzzy Q-learning

    Meng Joo Er;Chang Deng

  • PCA and LDA in DCT domain

    Weilong Chen;Meng Joo Er;Shiqian Wu

  • An Incremental Learning of Concept Drifts Using Evolving Type-2 Recurrent Fuzzy Neural Networks

    Mahardhika Pratama;Jie Lu;Edwin Lughofer;Guangquan Zhang

  • A fast and accurate online self-organizing scheme for parsimonious fuzzy neural networks

    Ning Wang;Meng Joo Er;Xianyao Meng

  • Global Asymptotic Model-Free Trajectory-Independent Tracking Control of an Uncertain Marine Vehicle: An Adaptive Universe-Based Fuzzy Control Approach

    Ning Wang;Shun-Feng Su;Jianchuan Yin;Zhongjiu Zheng

  • Review on deep learning techniques for marine object recognition: Architectures and algorithms

    Ning Wang;Yuanyuan Wang;Meng Joo Er

  • Event-Triggered Consensus of Linear Multiagent Systems With Time-Varying Communication Delays

    Chao Deng;Meng Joo Er;Guang-Hong Yang;Ning Wang

  • Composite adaptive fuzzy H∞ tracking control of uncertain nonlinear systems

    Yongping Pan;Yu Zhou;Tairen Sun;Meng Joo Er

  • Robust adaptive control of robot manipulators using generalized fuzzy neural networks

    Meng Joo Er;Yang Gao

Frequent Co-Authors

Ning Wang
Ning Wang Dalian Maritime University
Yang Gao
Yang Gao Google (United Kingdom)
Shiqian Wu
Shiqian Wu University of Victoria
Yongping Pan
Yongping Pan Sun Yat-sen University
Mahardhika Pratama
Mahardhika Pratama University of South Australia
Shun-Feng Su
Shun-Feng Su National Taiwan University of Science and Technology
Edwin Lughofer
Edwin Lughofer Johannes Kepler University of Linz
Douglas J. Leith
Douglas J. Leith Trinity College Dublin
Guang-Hong Yang
Guang-Hong Yang Northeastern University
Min Han
Min Han Dalian University of Technology

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