World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
37
Citations
7725
World Ranking
10573
National Ranking
190

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
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
Marc Pollefeys
Marc Pollefeys ETH Zurich

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