Marcin Piekarczyk

455 citations
32 papers · 203 · h-index 8

Impact in

Papers in

Marcin Piekarczyk

28 papers receiving 194 citations

Peers

Marcin Piekarczyk
Comparison fields: 5 of 59
  • Human-Computer Interaction 42
  • Computer Vision and Pattern Recognition 77
  • Nuclear and High Energy Physics 39
  • Signal Processing 23
  • Orthopedics and Sports Medicine 13
Replace Krzysztof Rzecki with:
Krzysztof Rzecki Poland
Adrian Muscat Malta
P. Paalanen Finland
Tai-Peng Tian United States
Miao Xin China
Chen Guo China
Hwasup Lim South Korea
Liang Chang China
P. Mazurek Poland
Adilson Gonzaga Brazil
Marcin Piekarczyk relative to Krzysztof Rzecki Poland Krzysztof Rzecki's profile →
Citations per field
00.5×2.6×
Krzysztof Rzecki · 1×
Citations per year

Countries citing papers authored by Marcin Piekarczyk

Since Specialization
Citations

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

Fields of papers citing papers by Marcin Piekarczyk

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Marcin Piekarczyk, 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 Marcin Piekarczyk Line = papers co-authored together Marcin Piekarczyk links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 32 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201744
2 201923
3
Dependence of Kinect sensors number and position on gestures recognition with Gesture Description Language semantic classifier
201317
4 201016
5 202015
6 201911
7 20219
8 20218
9 20137
10 20205
11 20175
12 20175
13 20254
14 20154
15 20124
16 20234
17 20213
18 20233
19 20183
20 20222

About Marcin Piekarczyk

Marcin Piekarczyk is a scholar working on Nuclear and High Energy Physics, Computer Vision and Pattern Recognition, Artificial Intelligence, Human-Computer Interaction and Information Systems, having authored 32 papers that have together received 203 indexed citations. Recurring topics across this work include Particle Detector Development and Performance (11 papers), Astrophysics and Cosmic Phenomena (11 papers), Dark Matter and Cosmic Phenomena (7 papers), Handwritten Text Recognition Techniques (5 papers), Hand Gesture Recognition Systems (4 papers), Human Pose and Action Recognition (4 papers), Biometric Identification and Security (3 papers) and Video Analysis and Summarization (3 papers). The work is most often cited by research in Human-Computer Interaction (42 citations), Computer Vision and Pattern Recognition (77 citations), Nuclear and High Energy Physics (39 citations), Signal Processing (23 citations) and Orthopedics and Sports Medicine (13 citations). Marcin Piekarczyk has collaborated with scholars based in Poland, Czechia and Hungary. Frequent co-authors include Tomasz Hachaj, Marek R. Ogiela, Łukasz Bibrzycki, Michał Niedźwiecki, Krzysztof Rzecki, P. Homola, David Alvarez-Castillo, Arman Tursunov, Alan R. Duffy and J. A. Zamora Saa. Their work appears in journals such as Sensors, Universe, Symmetry, Applied Sciences and Electronics.

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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