Tomáš Pevný

7.4k citations
59 papers · 3.1k indexed · 2 hit papers · h-index 22
Topics
Advanced Steganography and Watermarking Techniques (32 papers)Digital Media Forensic Detection (26 papers)Internet Traffic Analysis and Secure E-voting (22 papers)

In The Last Decade

Tomáš Pevný

59 papers receiving 2.9k citations

Hit Papers

Steganalysis by Subtractive Pixel Adjacency Matrix200920262014202020102009200400600

Peers

Tomáš Pevný
Comparison fields: 5 of 78
  • Computer Vision and Pattern Recognition 2.7k
  • Artificial Intelligence 785
  • Computer Networks and Communications 274
  • Signal Processing 257
  • Media Technology 182
Replace Benedetta Tondi with:
Benedetta Tondi Italy
Xiangyang Luo China
Guangjie Liu China
Fenlin Liu China
Jiangqun Ni China
Yuanman Li Macao
Arup Kumar Pal India
Lakshmanan Nataraj United States
Miroslav Goljan United States
Javaid A. Sheikh India
Tomáš Pevný relative to Benedetta Tondi Italy Benedetta Tondi's profile →
Citations per field
00.5×10×17.4×
Benedetta Tondi · 1×
Citations per year

Countries citing papers authored by Tomáš Pevný

Since Specialization
Citations

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

Fields of papers citing papers by Tomáš Pevný

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Tomáš Pevný

This figure shows the co-authorship network connecting the top 25 collaborators of Tomáš Pevný. A scholar is included among the top collaborators of Tomáš Pevný 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 Tomáš Pevný. Tomáš Pevný 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
#WorkIndexed citations
1 1
2 1
3 3
4 2
5 7
6 49
7 23
8 14
9 33
10 37
11 3
12 6
13 9
14 46
15 19
16 59
17 26
18 343
19 32
20 11

About Tomáš Pevný

Tomáš Pevný is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Signal Processing, having authored 59 papers that have together received 3.1k indexed citations. Recurring topics across this work include Advanced Steganography and Watermarking Techniques (32 papers), Digital Media Forensic Detection (26 papers) and Internet Traffic Analysis and Secure E-voting (22 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (2.7k citations), Artificial Intelligence (785 citations) and Signal Processing (257 citations). Tomáš Pevný has collaborated with scholars based in Czechia, United States and United Kingdom. Frequent co-authors include Jessica Fridrich, Patrick Bas, Andrew D. Ker, Jan Kodovský, Martin Grill, Martin Řehák, John Klein, Paul Prasse, Tobias Scheffer and Martin Holeňa. Their work appears in journals such as Expert Systems with Applications, Pattern Recognition and Machine Learning.

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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