Peter Sýkora

525 total citations
27 papers, 326 citations indexed

About

Peter Sýkora is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Neurology. According to data from OpenAlex, Peter Sýkora has authored 27 papers receiving a total of 326 indexed citations (citations by other indexed papers that have themselves been cited), including 18 papers in Computer Vision and Pattern Recognition, 9 papers in Artificial Intelligence and 4 papers in Neurology. Recurrent topics in Peter Sýkora's work include Human Pose and Action Recognition (7 papers), Video Surveillance and Tracking Methods (7 papers) and Anomaly Detection Techniques and Applications (4 papers). Peter Sýkora is often cited by papers focused on Human Pose and Action Recognition (7 papers), Video Surveillance and Tracking Methods (7 papers) and Anomaly Detection Techniques and Applications (4 papers). Peter Sýkora collaborates with scholars based in Slovakia and Pakistan. Peter Sýkora's co-authors include Patrik Kamencay, Róbert Hudec and Miroslav Benčo and has published in prestigious journals such as SHILAP Revista de lepidopterología, Sensors and Applied Sciences.

In The Last Decade

Peter Sýkora

22 papers receiving 304 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Peter Sýkora Slovakia 8 189 97 34 32 24 27 326
Sareer Ul Amin South Korea 11 120 0.6× 125 1.3× 33 1.0× 30 0.9× 41 1.7× 15 377
Simone Angarano Italy 6 199 1.1× 98 1.0× 56 1.6× 36 1.1× 11 0.5× 10 289
R Meghana India 4 115 0.6× 73 0.8× 22 0.6× 14 0.4× 12 0.5× 6 350
Herman Herman Indonesia 11 134 0.7× 51 0.5× 28 0.8× 17 0.5× 26 1.1× 60 341
Hongxia Xie Taiwan 8 188 1.0× 91 0.9× 22 0.6× 33 1.0× 14 0.6× 17 346
Rin-ichiro Taniguchi Japan 11 263 1.4× 67 0.7× 35 1.0× 11 0.3× 20 0.8× 39 391
V. Kalist India 6 157 0.8× 44 0.5× 26 0.8× 59 1.8× 14 0.6× 18 318
Adnan Ahmed Rafique Pakistan 10 353 1.9× 101 1.0× 55 1.6× 41 1.3× 20 0.8× 15 481
G Divya India 3 98 0.5× 68 0.7× 24 0.7× 12 0.4× 9 0.4× 6 327

Countries citing papers authored by Peter Sýkora

Since Specialization
Citations

This map shows the geographic impact of Peter Sýkora'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 Peter Sýkora with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Peter Sýkora more than expected).

Fields of papers citing papers by Peter Sýkora

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Peter Sýkora. 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 Peter Sýkora. The network helps show where Peter Sýkora may publish in the future.

Co-authorship network of co-authors of Peter Sýkora

This figure shows the co-authorship network connecting the top 25 collaborators of Peter Sýkora. A scholar is included among the top collaborators of Peter Sýkora 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 Peter Sýkora. Peter Sýkora is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
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Sýkora, Peter, et al.. (2024). Overview and Comparison of Deep Neural Networks for Wildlife Recognition Using Infrared Images. SHILAP Revista de lepidopterología. 5(4). 2801–2828.
3.
Kamencay, Patrik, et al.. (2024). Automated Method for Intracranial Aneurysm Classification Using Deep Learning. Sensors. 24(14). 4556–4556.
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Kamencay, Patrik, et al.. (2024). Recognition of Dangerous Objects using Deep Learning. 1 indexed citations
6.
Kamencay, Patrik, et al.. (2023). A New Deep-Learning Method for Human Activity Recognition. Sensors. 23(5). 2816–2816. 33 indexed citations
7.
Kamencay, Patrik, et al.. (2023). Automated Detection of Cerebral Aneurysms using Deep Learning Techniques. 75–78. 2 indexed citations
8.
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Kamencay, Patrik, et al.. (2023). A New Approach for Aneurysm Detection Based on CNNs. 21. 71–74. 1 indexed citations
10.
Kamencay, Patrik, et al.. (2023). A New Method for Detection of Cerebral Aneurysm using Deep Learning. 1–1. 2 indexed citations
11.
Hudec, Róbert, et al.. (2022). Human Activity Classification Using the 3DCNN Architecture. Applied Sciences. 12(2). 931–931. 64 indexed citations
12.
Hudec, Róbert, et al.. (2022). A New Approach for Abnormal Human Activities Recognition Based on ConvLSTM Architecture. Sensors. 22(8). 2946–2946. 30 indexed citations
13.
Sýkora, Peter, et al.. (2020). Comparison of convolutional neural network in Python environment on CPU and GPU. 1. 1–4. 1 indexed citations
14.
Hudec, Róbert, et al.. (2020). Violent Behavioral Activity Classification Using Artificial Neural Network. 1–5. 4 indexed citations
15.
Sýkora, Peter, et al.. (2020). Comparison of Neural Networks with Feature Extraction Methods for Depth Map Classification. 15(1). 67–83. 4 indexed citations
16.
Sýkora, Peter, et al.. (2019). Artificial Neural Networks in Educational Process. 751–756.
17.
Sýkora, Peter, et al.. (2019). Development of a system for collecting and processing sky images and meteorological data used for weather prediction. Transportation research procedia. 40. 1548–1554. 4 indexed citations
18.
Kamencay, Patrik, et al.. (2018). Advanced point cloud estimation based on multiple view geometry. 10214. 1–5. 3 indexed citations
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20.
Kamencay, Patrik, et al.. (2015). An Efficient P-KCCA Algorithm for 2D-3D Face Recognition Using SVM. Advances in Electrical and Electronic Engineering. 13(4). 1 indexed citations

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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