World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
44
Citations
8550
World Ranking
7545
National Ranking
238

Ferdous Sohel 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 Ferdous Sohel 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: 265 publications — 66th percentile

66% of scientists in this discipline score the same or lower.

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

Ferdous Sohel 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 Ferdous Sohel 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: 44 D-Index — 48th percentile

48% of scientists in this discipline score the same or lower.

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

Overview

Ferdous Sohel is affiliated with Murdoch University in Australia and has contributed extensively to fields intersecting computer science and engineering. Their research output spans multiple areas including computer vision, artificial intelligence, and plant science, with a focus on applications such as smart agriculture and advanced neural networks.

Their main fields of study include:

  • Computer Science
  • Engineering

Subfields of Sohel's work encompass:

  • Computer Vision and Pattern Recognition
  • Artificial Intelligence
  • Plant Science
  • Electrical and Electronic Engineering
  • Radiology, Nuclear Medicine and Imaging

Core research topics addressed by Sohel cover:

  • Smart Agriculture and AI
  • Adversarial Robustness in Machine Learning
  • Domain Adaptation and Few-Shot Learning
  • Advanced Neural Network Applications
  • 3D Shape Modeling and Analysis
  • Advanced Image and Video Retrieval Techniques
  • Anomaly Detection Techniques and Applications

Frequent collaborators in Sohel's research include:

  • Mohammed Bennamoun
  • Dean Diepeveen
  • Hamid Laga
  • M. G. K. Jones
  • Farid Boussaïd

The scientist's publications have featured repeatedly in venues such as:

  • arXiv (Cornell University)
  • Neurocomputing
  • Computers and Electronics in Agriculture
  • IEEE Access
  • Ecological Informatics

Representative recent papers include:

  • Leveraging Auxiliary Tasks with Affinity Learning for Weakly Supervised Semantic Segmentation, 2021, 2021 IEEE/CVF International Conference on Computer Vision (ICCV)
  • A review of the uses of virtual reality in engineering education, 2020, Computer Applications in Engineering Education
  • CurveNet: Curvature-Based Multitask Learning Deep Networks for 3D Object Recognition, 2020, IEEE/CAA Journal of Automatica Sinica
  • Plant disease recognition in a low data scenario using few-shot learning, 2024, Computers and Electronics in Agriculture
  • A Pixel Distribution Remapping and Multi-Prior Retinex Variational Model for Underwater Image Enhancement, 2024, IEEE Transactions on Multimedia

Best Publications

  • Cost-Sensitive Learning of Deep Feature Representations From Imbalanced Data

    Salman H. Khan;Munawar Hayat;Mohammed Bennamoun;Ferdous A. Sohel

  • A New Representation of Skeleton Sequences for 3D Action Recognition

    Qiuhong Ke;Mohammed Bennamoun;Senjian An;Ferdous Sohel

  • A Comprehensive Survey of Deep Learning for Image Captioning

    Md. Zakir Hossain;Ferdous Sohel;Mohd Fairuz Shiratuddin;Hamid Laga

  • Rotational Projection Statistics for 3D Local Surface Description and Object Recognition

    Yulan Guo;Yulan Guo;Ferdous Ahmed Sohel;Mohammed Bennamoun;Min Lu

  • 3D Object Recognition in Cluttered Scenes with Local Surface Features: A Survey

    Yulan Guo;Mohammed Bennamoun;Ferdous Ahmed Sohel;Min Lu

  • A Comprehensive Performance Evaluation of 3D Local Feature Descriptors

    Yulan Guo;Mohammed Bennamoun;Ferdous Sohel;Min Lu

  • A survey of deep learning techniques for weed detection from images

    A S M Mahmudul Hasan;Ferdous Sohel;Dean Diepeveen;Dean Diepeveen;Hamid Laga

  • Automatic Shadow Detection and Removal from a Single Image

    Salman H. Khan;Mohammed Bennamoun;Ferdous Sohel;Roberto Togneri

  • Learning Clip Representations for Skeleton-Based 3D Action Recognition

    Qiuhong Ke;Mohammed Bennamoun;Senjian An;Ferdous Sohel

  • SkeletonNet: Mining Deep Part Features for 3-D Action Recognition

    Qiuhong Ke;Senjian An;Mohammed Bennamoun;Ferdous Sohel

  • An Accurate and Robust Range Image Registration Algorithm for 3D Object Modeling

    Yulan Guo;Ferdous Ahmed Sohel;Mohammed Bennamoun;Jianwei Wan

  • A Discriminative Representation of Convolutional Features for Indoor Scene Recognition

    Salman H. Khan;Munawar Hayat;Mohammed Bennamoun;Roberto Togneri

  • Leveraging Auxiliary Tasks with Affinity Learning for Weakly Supervised Semantic Segmentation

    Lian Xu;Wanli Ouyang;Mohammed Bennamoun;Farid Boussaid

  • Leveraging Auxiliary Tasks with Affinity Learning for Weakly Supervised Semantic Segmentation

    Lian Xu;Wanli Ouyang;Mohammed Bennamoun;Farid Boussaid

  • RGB-D Object Recognition and Grasp Detection Using Hierarchical Cascaded Forests

    Umar Asif;Mohammed Bennamoun;Ferdous A. Sohel

  • Automatic Feature Learning for Robust Shadow Detection

    Salman Hameed Khan;Mohammed Bennamoun;Ferdous Sohel;Roberto Togneri

  • NormalNet: A voxel-based CNN for 3D object classification and retrieval

    Cheng Wang;Ming Cheng;Ferdous Sohel;Mohammed Bennamoun

  • A novel local surface feature for 3D object recognition under clutter and occlusion

    Yulan Guo;Yulan Guo;Ferdous Ahmed Sohel;Mohammed Bennamoun;Jianwei Wan

  • A review of the uses of virtual reality in engineering education

    Jaiden A. di Lanzo;Andrew Valentine;Ferdous Sohel;Angie Y. T. Yapp

  • Machine learning-based prediction of heart failure readmission or death: implications of choosing the right model and the right metrics.

    Saqib Ejaz Awan;Mohammed Bennamoun;Ferdous Sohel;Frank Mario Sanfilippo

  • An Integrated Framework for 3-D Modeling, Object Detection, and Pose Estimation From Point-Clouds

    Yulan Guo;Mohammed Bennamoun;Ferdous Sohel;Min Lu

  • Coral classification with hybrid feature representations

    A. Mahmood;M. Bennamoun;S. An;F. Sohel

  • A Pixel Distribution Remapping and Multi-Prior Retinex Variational Model for Underwater Image Enhancement

    Unknown

  • Machine learning in heart failure: ready for prime time.

    Saqib Ejaz Awan;Ferdous Sohel;Frank Mario Sanfilippo;Mohammed Bennamoun

Frequent Co-Authors

Mohammed Bennamoun
Mohammed Bennamoun University of Western Australia
Roberto Togneri
Roberto Togneri University of Western Australia
Farid Boussaid
Farid Boussaid University of Western Australia
Yulan Guo
Yulan Guo Sun Yat-sen University
Guojun Lu
Guojun Lu Federation University Australia
Gary A. Kendrick
Gary A. Kendrick University of Western Australia
Robert B. Fisher
Robert B. Fisher University of Edinburgh
Munawar Hayat
Munawar Hayat Monash University
Jonathan Li
Jonathan Li University of Waterloo
Xuming He
Xuming He Washington University in St. Louis

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