Nicolai Petkov

6.6k total citations · 2 hit papers
137 papers, 4.2k citations indexed

About

Nicolai Petkov is a scholar working on Computer Vision and Pattern Recognition, Cognitive Neuroscience and Artificial Intelligence. According to data from OpenAlex, Nicolai Petkov has authored 137 papers receiving a total of 4.2k indexed citations (citations by other indexed papers that have themselves been cited), including 60 papers in Computer Vision and Pattern Recognition, 26 papers in Cognitive Neuroscience and 22 papers in Artificial Intelligence. Recurrent topics in Nicolai Petkov's work include Advanced Image and Video Retrieval Techniques (22 papers), Image Retrieval and Classification Techniques (19 papers) and Visual perception and processing mechanisms (18 papers). Nicolai Petkov is often cited by papers focused on Advanced Image and Video Retrieval Techniques (22 papers), Image Retrieval and Classification Techniques (19 papers) and Visual perception and processing mechanisms (18 papers). Nicolai Petkov collaborates with scholars based in Netherlands, Italy and Spain. Nicolai Petkov's co-authors include George Azzopardi, Nicola Strisciuglio, Mario Vento, Cosmin Grigorescu, Michel A. Westenberg, Giuseppe Pápari, P. Kruizinga, Michael Biehl, Alessia Saggese and Marcel F. Jonkman and has published in prestigious journals such as PLoS ONE, IEEE Transactions on Pattern Analysis and Machine Intelligence and IEEE Transactions on Image Processing.

In The Last Decade

Nicolai Petkov

128 papers receiving 4.0k citations

Hit Papers

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What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

Trainable COSFIRE filters for vessel delineation with application to retinal images

2014 533 citations George Azzopardi, Nicola Strisciuglio et al. Medical Image Analysis profile →
Survey of feature selection and extraction techniques for stock market prediction

2023 98 citations Michael Biehl, Nicolai Petkov et al. Financial Innovation profile →

Peers

Countries citing papers authored by Nicolai Petkov

Since Specialization

Citations

This map shows the geographic impact of Nicolai Petkov's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Nicolai Petkov with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Nicolai Petkov more than expected).

Fields of papers citing papers by Nicolai Petkov

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Nicolai Petkov. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Nicolai Petkov. The network helps show where Nicolai Petkov may publish in the future.

Co-authorship network of co-authors of Nicolai Petkov

This figure shows the co-authorship network connecting the top 25 collaborators of Nicolai Petkov. A scholar is included among the top collaborators of Nicolai Petkov based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Nicolai Petkov. Nicolai Petkov is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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20 of 20 papers shown

#	Work	Indexed citations
1	Forecasting relative returns for S&P 500 stocks using machine learning 2024 ·Financial Innovation ·(unknown), Michael Biehl, Nicolai Petkov	14
2	Survey of feature selection and extraction techniques for stock market prediction breakdown → 2023 ·Financial Innovation ·(unknown), Michael Biehl, Nicolai Petkov	98
3	AReN: A Deep Learning Approach for Sound Event Recognition Using a Brain Inspired Representation 2020 ·IEEE Transactions on Information Forensics and Security ·Antonio Greco, Nicolai Petkov, Alessia Saggese, Mario Vento	43
4	Enhanced robustness of convolutional networks with a push–pull inhibition layer 2020 ·Neural Computing and Applications ·Nicola Strisciuglio, Manuel López-Antequera, Nicolai Petkov	20
5	Hierarchical Approach to Classify Food Scenes in Egocentric Photo-Streams 2019 ·IEEE Journal of Biomedical and Health Informatics ·(unknown), (unknown), Md. Mostafa Kamal Sarker, Domènec Puig, Nicolai Petkov, Petia Radeva	9
6	Place and Object Recognition by CNN-Based COSFIRE Filters 2019 ·IEEE Access ·Manuel López-Antequera, (unknown), Nicola Strisciuglio, Nicolai Petkov	7
7	Using Neural Networks with Routine Health Records to Identify Suicide Risk: Feasibility Study 2018 ·JMIR Mental Health ·Marcos DelPozo‐Baños, Ann John, Nicolai Petkov, Damon Berridge, (unknown), Keith Lloyd, Caroline Jones, (unknown), Carlos M. Travieso	42
8	Assigning pigs to uniform target weight groups using machine learning 2018 ·Socio-Environmental Systems Modeling ·(unknown), George Azzopardi, B.J. Ducro, R.F. Veerkamp, Nicolai Petkov	1
9	Detection of u-serrated patterns in direct immunofluorescence images of autoimmune bullous diseases by inhibition-augmented COSFIRE filters 2018 ·International Journal of Medical Informatics ·Chenyu Shi, Joost M. Meijer, Jiapan Guo, George Azzopardi, Gilles F.H. Diercks, Enno Schmidt, Detlef Zillikens, Marcel F. Jonkman, Nicolai Petkov	4
10	Computer analysis of images and patterns : 16th international conference, CAIP 2015 valletta, malta, september 2-4, 2015 proceedings, part II 2015 ·Lecture notes in computer science ·George Azzopardi, Nicolai Petkov	5
11	Multiscale Blood Vessel Delineation Using B-COSFIRE Filters 2015 ·Lecture notes in computer science ·Nicola Strisciuglio, George Azzopardi, Mario Vento, Nikolay Petkov, Nicolai Petkov	15
12	Trainable COSFIRE filters for vessel delineation with application to retinal images breakdown → 2014 ·Medical Image Analysis ·George Azzopardi, Nicola Strisciuglio, Mario Vento, Nicolai Petkov	533
13	Contour Detection by Surround Inhibition in the Circular Harmonic Functions Domain 2006 ·University of Groningen research database (University of Groningen / Centre for Information Technology) ·Giuseppe Pápari, Patrizio Campisi, Nicolai Petkov, Alessandro Neri	2
14	LVQ acrosome integrity assessment of boar sperm cells 2006 ·University of Groningen research database (University of Groningen / Centre for Information Technology) ·Nicolai Petkov, Enrique Alegre, Michael Biehl, Lídia Sánchez-González	7
15	2006 IEEE INTERNATIONAL CONFERENCE ON IMAGE PROCESSING, ICIP 2006, PROCEEDINGS 2006 ·International Conference on Image Processing ·Giuseppe Pápari, Patrizio Campisi, Nicolai Petkov, Alessandro Neri	10
16	Gabor filtering augmented with surround inhibition for improved contour detection by texture suppression 2004 ·University of Groningen research database (University of Groningen / Centre for Information Technology) ·Nicolai Petkov, Martijn Wieling	2
17	Band-limited noise suppresses contour perception not only of letters but of any objects 2004 ·Perception ·Nicolai Petkov, Michel A. Westenberg	2
18	The role of non-CRF inhibition in contour detection 2003 ·Digital Library (University of West Bohemia) ·Cosmin Grigorescu, Nicolai Petkov, Michel A. Westenberg	4
19	Distance sets for shape filters and shape recognition 2003 ·IEEE Transactions on Image Processing ·Cosmin Grigorescu, Nicolai Petkov	156
20	Statistical analysis of simulation-generated time series 1992 ·Default journal ·(unknown), Thomas Lippert, Nicolai Petkov, Klaus Schilling	1

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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