World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
36
Citations
6579
World Ranking
11129
National Ranking
336

Brijesh Verma 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 Brijesh Verma 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: 250 publications — 62nd percentile

62% of scientists in this discipline score the same or lower.

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

Brijesh Verma 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 Brijesh Verma 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

Brijesh Verma is affiliated with Central Queensland University in Australia and specializes in computer science, with a significant focus on computer vision and pattern recognition. Their research portfolio spans 54 publications within this primary field, reflecting a consistent engagement with topics related to advanced neural network applications and machine learning techniques.

Their work covers several key areas including:

  • Advanced Neural Network Applications
  • Advanced Image and Video Retrieval Techniques
  • Face and Expression Recognition
  • Multimodal Machine Learning Applications
  • Domain Adaptation and Few-Shot Learning
  • Machine Learning and Data Classification
  • Metaheuristic Optimization Algorithms Research

Brijesh Verma has contributed research papers published in journals and conferences such as:

  • Autonomous deep feature extraction based method for epileptic EEG brain seizure classification, 2021, Neurocomputing
  • Single class detection-based deep learning approach for identification of road safety attributes, 2021, Neural Computing and Applications
  • Multiple strong and balanced cluster-based ensemble of deep learners, 2020, Pattern Recognition
  • A non-specialized ensemble classifier using multi-objective optimization, 2020, Neurocomputing
  • Prediction of Students' Performance in e-Learning Environment using Data Mining/ Machine Learning Techniques, 2021, Journal of University of Shanghai for Science and Technology

Frequent coauthors associated with Brijesh Verma include:

  • Basim Azam (11 collaborations)
  • Ranju Mandal (6 collaborations)
  • Pubudu Sanjeewani (5 collaborations)
  • Ashfaqur Rahman (5 collaborations)
  • Lipo Wang (5 collaborations)

The researcher has regularly published in venues such as:

  • IEEE Access (3 publications)
  • Neurocomputing (2 publications)
  • Information Sciences (2 publications)
  • 2022 IEEE Symposium Series on Computational Intelligence (SSCI) (2 publications)
  • arXiv (Cornell University) (2 publications)

Best Publications

  • Facial Expression Analysis under Partial Occlusion: A Survey

    Ligang Zhang;Brijesh Verma;Dian Tjondronegoro;Vinod Chandran

  • A computer-aided diagnosis system for digital mammograms based on fuzzy-neural and feature extraction techniques

    B. Verma;J. Zakos

  • A novel feature extraction technique for the recognition of segmented handwritten characters

    M. Blumenstein;B. Verma;H. Basli

  • On-Tree Mango Fruit Size Estimation Using RGB-D Images

    Zhenglin Wang;Kerry B. Walsh;Brijesh K. Verma

  • Neural vs. statistical classifier in conjunction with genetic algorithm based feature selection

    Ping Zhang;Brijesh Verma;Kuldeep Kumar

  • Monthly Rainfall Forecasting Using One-Dimensional Deep Convolutional Neural Network

    Ali Haidar;Brijesh Verma

  • Classification of benign and malignant patterns in digital mammograms for the diagnosis of breast cancer

    Brijesh Verma;Peter McLeod;Alan Klevansky

  • A modified direction feature for cursive character recognition

    M. Blumenstein;X.Y. Liu;B. Verma

  • Cluster-Oriented Ensemble Classifier: Impact of Multicluster Characterization on Ensemble Classifier Learning

    B. Verma;A. Rahman

  • Fast training of multilayer perceptrons

    B. Verma

  • Impact of Automatic Feature Extraction in Deep Learning Architecture

    Fatma Shaheen;Brijesh Verma;Md. Asafuddoula

  • A novel neural-genetic algorithm to find the most significant combination of features in digital mammograms

    Brijesh Verma;Ping Zhang

  • Novel Layered Clustering-Based Approach for Generating Ensemble of Classifiers

    A Rahman;B Verma

  • A Neural Network based Technique for Automatic Classification of Road Cracks

    J. Bray;B. Verma;Xue Li;Wade He

  • A novel soft cluster neural network for the classification of suspicious areas in digital mammograms

    Brijesh Verma;Peter McLeod;Alan Klevansky

  • An investigation of the modified direction feature for cursive character recognition

    Michael Blumenstein;Xin Yu Liu;Brijesh Verma

  • Handwritten Hindi character recognition using multilayer perceptron and radial basis function neural networks

    B.K. Verma

  • Ensemble classifier generation using non-uniform layered clustering and Genetic Algorithm

    Ashfaqur Rahman;Brijesh Verma

  • Fusion of multiple handwritten word recognition techniques

    Brijesh K. Verma;Paul D. Gader;Wen-Tsong Chen

  • Binary segmentation algorithm for English cursive handwriting recognition

    Hong Lee;Brijesh Verma

Frequent Co-Authors

Michael Blumenstein
Michael Blumenstein University of Technology Sydney
Mengjie Zhang
Mengjie Zhang Victoria University of Wellington
Xin Yao
Xin Yao Lingnan University
Kerry B. Walsh
Kerry B. Walsh Central Queensland University
Paul D. Gader
Paul D. Gader University of Florida
Xue Li
Xue Li University of Queensland
Vinod Chandran
Vinod Chandran Queensland University of Technology
Kenji Doya
Kenji Doya Okinawa Institute of Science and Technology
Andrzej Cichocki
Andrzej Cichocki Systems Research Institute
Sabri Arik
Sabri Arik Istanbul University

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