S Fazekas

26 papers receiving 514 citations

Peers

S Fazekas
Comparison fields: 5 of 76
  • Computer Vision and Pattern Recognition 357
  • Computational Mechanics 72
  • Computer Graphics and Computer-Aided Design 45
  • Safety, Risk, Reliability and Quality 44
  • Signal Processing 39
Replace Yunyi Li with:
Yunyi Li China
Yibin Tian China
Zewei He China
Marina Nicolas France
В. М. Карташов Ukraine
Ruggero Pintus Italy
Iman Sadeghi United States
Shaofei Wang China
Ping Tan China
Pierre Jacquot Switzerland
S Fazekas relative to Yunyi Li China Yunyi Li's profile →
Citations per field
00.5×10×15×
Yunyi Li · 1×
Citations per year

Countries citing papers authored by S Fazekas

Since Specialization
Citations

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

Fields of papers citing papers by S Fazekas

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of S Fazekas

This figure shows the co-authorship network connecting the top 25 collaborators of S Fazekas. A scholar is included among the top collaborators of S Fazekas 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 S Fazekas. S Fazekas 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
1 203
2 21
3 3
4 33
5 26
6 9
7 23
8 27
9 13
10 18
11 15
12 1
13
Presence of phospho-tyrosine in alkaline hydrolysate of pig skeletal muscle myosin.
1
14
A new concept in the molecular process of muscle contraction: functional role of phosphorylated amino acids in myosin.
1
15
Presence of covalently bound energy-rich phosphates in human tracheal smooth muscle myosin.
1
16
Purification and properties of myosin from the "hatching muscle" (m. complexus) of geese.
2
17 6
18
Purification and phosphate content of slow-twitch human myosin and its possible role in the maintenance of muscle function.
1
19 3
20
Surgical drainage of a submandibular air sac in an orangutan.
5

About S Fazekas

S Fazekas is a scholar working on Computer Vision and Pattern Recognition, Cell Biology and Management, Monitoring, Policy and Law, having authored 26 papers that have together received 527 indexed citations. Recurring topics across this work include Advanced Vision and Imaging (8 papers), Muscle metabolism and nutrition (5 papers) and Image Enhancement Techniques (5 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (357 citations), Computer Graphics and Computer-Aided Design (45 citations) and Computational Mathematics (7 citations). S Fazekas has collaborated with scholars based in Hungary, Germany and Israel. Frequent co-authors include Mark J. Huiskes, Renaud Péteri, Dmitry Chetverikov, János Kertész, Dietrich E. Wolf, János Török, József Molnár, Nahum Kiryati, Henning Arendt Knudsen and Michal Haindl. Their work appears in journals such as Journal of Computational Physics, International Journal of Computer Vision and Pattern Recognition Letters.

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.

Explore authors with similar magnitude of impact

Rankless by CCL
2026