M. Sigut

444 citations
30 papers · 289 · h-index 9

Impact in

Papers in

M. Sigut

23 papers receiving 269 citations

Peers

M. Sigut
Comparison fields: 5 of 69
  • Computer Vision and Pattern Recognition 126
  • Control and Systems Engineering 141
  • Media Technology 19
  • Aerospace Engineering 50
  • Biomedical Engineering 65
Replace Xiaowei Tu with:
Xiaowei Tu China
Zhehao Jin China
J. Bao China
Kunming Zheng China
Min‐Fan Ricky Lee Taiwan
Sergey A. Kolyubin Russia
Mahmut Di̇ri̇k Türkiye
Chunsheng Hua China
Nate Koenig United States
Vadim Zhmud Russia
M. Sigut relative to Xiaowei Tu China Xiaowei Tu's profile →
Citations per field
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Xiaowei Tu · 1×
Citations per year

Countries citing papers authored by M. Sigut

Since Specialization
Citations

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

Fields of papers citing papers by M. Sigut

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 15 scholars most cited alongside M. Sigut, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with M. Sigut Line = papers co-authored together M. Sigut links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 30 papers — load more, or switch the sort, to bring in the rest.

#Work
1 200390
2 200154
3 202034
4 200621
5 200813
6 201413
7 200912
8 202010
9 20148
10 20026
11 20165
12 20024
13 19993
14 20003
15 20062
16 20062
17 20082
18 20042
19
A control engineering laboratory based on a low-cost non-linear plant
20061
20 20081

About M. Sigut

M. Sigut is a scholar working on Control and Systems Engineering, Computer Vision and Pattern Recognition, Computer Networks and Communications, Artificial Intelligence and Atomic and Molecular Physics, and Optics, having authored 30 papers that have together received 289 indexed citations. Recurring topics across this work include Adaptive Control of Nonlinear Systems (6 papers), Advanced Vision and Imaging (4 papers), Advanced Control Systems Optimization (3 papers), Fault Detection and Control Systems (3 papers), Adaptive optics and wavefront sensing (3 papers), Advanced Control Systems Design (3 papers), Experimental Learning in Engineering (3 papers) and Robotic Path Planning Algorithms (3 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (126 citations), Control and Systems Engineering (141 citations), Media Technology (19 citations), Aerospace Engineering (50 citations) and Biomedical Engineering (65 citations). M. Sigut has collaborated with scholars based in Spain and United Kingdom. Frequent co-authors include Juan Albino Méndez Pérez, G.N. Marichal, Rafael Arnay, José Sigut, L. Moreno, Jonay Toledo, Silvia Alayón, Evelio J. González, A. Hamilton and Pedro Toledo. Their work appears in journals such as Electronics Letters, Sensors, Journal of Cleaner Production, European Journal of Engineering Education and Fuzzy Sets and Systems.

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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