World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
37
Citations
7725
World Ranking
10571
National Ranking
190

Nicolai Petkov 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 Nicolai Petkov 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: 245 publications — 61st percentile

61% of scientists in this discipline score the same or lower.

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

Nicolai Petkov 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 Nicolai Petkov 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: 37 D-Index — 27th percentile

27% of scientists in this discipline score the same or lower.

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

Overview

Nicolai Petkov is affiliated with the University of Groningen in the Netherlands, with a research focus in the field of Computer Science. Their work spans multiple subfields, primarily in Computer Vision and Pattern Recognition, Cognitive Neuroscience, Aerospace Engineering, Management Science and Operations Research, and Artificial Intelligence. The breadth of their research includes the development and application of computational methods across these areas.

The scientist has published extensively in frequent venues including arXiv (Cornell University), Zenodo (CERN European Organization for Nuclear Research), Financial Innovation, Expert Systems with Applications, and Imaging Neuroscience. These platforms reflect the interdisciplinary nature of their research contributions.

Nicolai Petkov has contributed to key topics such as:

  • Advanced Image and Video Retrieval Techniques
  • Robotics and Sensor-Based Localization
  • Advanced Vision and Imaging
  • EEG and Brain-Computer Interfaces
  • Advanced Image Processing Techniques
  • Stock Market Forecasting Methods
  • Forecasting Techniques and Applications

Among their notable recent papers are:

  • "Survey of feature selection and extraction techniques for stock market prediction," 2023, Financial Innovation
  • "A framework for feature selection through boosting," 2021, Expert Systems with Applications
  • "AReN: A Deep Learning Approach for Sound Event Recognition Using a Brain Inspired Representation," 2020, IEEE Transactions on Information Forensics and Security
  • "Virtual Reality for Pain Management in Cancer: A Comprehensive Review," 2020, IEEE Access
  • "Enhanced robustness of convolutional networks with a push-pull inhibition layer," 2020, Neural Computing and Applications

The scientist has collaborated frequently with colleagues Nicola Strisciuglio, David Fernandez-Chaves, José-Raúl Ruiz-Sarmiento, Javier González-Jiménez, and George Azzopardi, indicating a network of sustained co-authorship and interdisciplinary research partnerships.

In addition to papers, Nicolai Petkov has a book published by Springer Science+Business Media titled "Brain-Inspired Computing," released in 2021.

Best Publications

  • Comparison of texture features based on Gabor filters

    S.E. Grigorescu;N. Petkov;P. Kruizinga

  • Trainable COSFIRE filters for vessel delineation with application to retinal images

    George Azzopardi;Nicola Strisciuglio;Mario Vento;Nicolai Petkov

  • Contour detection based on nonclassical receptive field inhibition

    C. Grigorescu;N. Petkov;M.A. Westenberg

  • Review article: Edge and line oriented contour detection: State of the art

    Giuseppe Papari;Nicolai Petkov

  • MED-NODE

    Ioannis Giotis;Nynke Molders;Sander Land;Michael Biehl

  • Distance sets for shape filters and shape recognition

    C. Grigorescu;N. Petkov

  • Contour and boundary detection improved by surround suppression of texture edges

    Cosmin Grigorescu;Nicolai Petkov;Michel A. Westenberg

  • Nonlinear operator for oriented texture

    P. Kruizinga;N. Petkov

  • Audio Surveillance of Roads: A System for Detecting Anomalous Sounds

    Pasquale Foggia;Nicolai Petkov;Alessia Saggese;Nicola Strisciuglio

  • Reliable detection of audio events in highly noisy environments

    Pasquale Foggia;Nicolai Petkov;Alessia Saggese;Nicola Strisciuglio

  • Systolic parallel processing

    N. Petkov

  • A framework for feature selection through boosting

    Ahmad Alsahaf;Nicolai Petkov;Vikram Shenoy;George Azzopardi

  • Comparison of texture features based on Gabor filters

    P. Kruizinga;N. Petkov;S.E. Grigorescu

  • Suppression of contour perception by band-limited noise and its relation to nonclassical receptive field inhibition.

    Nicolai Petkov;Michel A. Westenberg

  • Trainable COSFIRE Filters for Keypoint Detection and Pattern Recognition

    G. Azzopardi;N. Petkov

  • Artistic Edge and Corner Enhancing Smoothing

    G. Papari;N. Petkov;P. Campisi

  • A CORF computational model of a simple cell that relies on LGN input outperforms the Gabor function model

    George Azzopardi;Nicolai Petkov

  • A biologically motivated multiresolution approach to contour detection

    Giuseppe Papari;Patrizio Campisi;Nicolai Petkov;Alessandro Neri

  • Automatic detection of vascular bifurcations in segmented retinal images using trainable COSFIRE filters

    George Azzopardi;Nicolai Petkov

  • Supervised vessel delineation in retinal fundus images with the automatic selection of B-COSFIRE filters

    Nicola Strisciuglio;George Azzopardi;Mario Vento;Nicolai Petkov

  • Motion detection, noise reduction, texture suppression, and contour enhancement by spatiotemporal Gabor filters with surround inhibition

    Nicolai Petkov;Easwar Subramanian

  • Learning effective color features for content based image retrieval in dermatology

    Kerstin Bunte;Michael Biehl;Marcel F. Jonkman;Nicolai Petkov

  • Appearance-invariant place recognition by discriminatively training a convolutional neural network

    Manuel Lopez-Antequera;Ruben Gomez-Ojeda;Nicolai Petkov;Javier Gonzalez-Jimenez

  • A CORF Computational Model of a Simple Cell

    George Azzopardi;Nicolai Petkov

Frequent Co-Authors

Patrizio Campisi
Patrizio Campisi Roma Tre University
Mario Vento
Mario Vento University of Salerno
Petia Radeva
Petia Radeva University of Barcelona
Marcel F. Jonkman
Marcel F. Jonkman University Medical Center Groningen
Javier Gonzalez-Jimenez
Javier Gonzalez-Jimenez University of Malaga
Xiaoyi Jiang
Xiaoyi Jiang University of Münster
Roel F. Veerkamp
Roel F. Veerkamp Wageningen University & Research
Marco Aiello
Marco Aiello University of Stuttgart
Justus Piater
Justus Piater University of Innsbruck
Katrin Amunts
Katrin Amunts Forschungszentrum Jülich

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