Zbigniew Leś

1.8k total citations
28 papers, 179 citations indexed

About

Zbigniew Leś is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Industrial and Manufacturing Engineering. According to data from OpenAlex, Zbigniew Leś has authored 28 papers receiving a total of 179 indexed citations (citations by other indexed papers that have themselves been cited), including 17 papers in Computer Vision and Pattern Recognition, 4 papers in Artificial Intelligence and 4 papers in Industrial and Manufacturing Engineering. Recurrent topics in Zbigniew Leś's work include Image Retrieval and Classification Techniques (15 papers), Image Processing and 3D Reconstruction (9 papers) and Manufacturing Process and Optimization (3 papers). Zbigniew Leś is often cited by papers focused on Image Retrieval and Classification Techniques (15 papers), Image Processing and 3D Reconstruction (9 papers) and Manufacturing Process and Optimization (3 papers). Zbigniew Leś collaborates with scholars based in Australia, United States and Canada. Zbigniew Leś's co-authors include Janel Swain, Andrea Darzi, Eddy Lang, David Zideman, Jestin N. Carlson, Samer G. Karam, Jan Brożek, Eunice M. Singletary, Nathan P. Charlton and Jonathan L. Epstein and has published in prestigious journals such as IEEE Transactions on Knowledge and Data Engineering, SAE technical papers on CD-ROM/SAE technical paper series and BMC Health Services Research.

In The Last Decade

Zbigniew Leś

19 papers receiving 93 citations

Peers

Zbigniew Leś
Comparison fields: 5 of 49
  • Computer Vision and Pattern Recognition 113
  • Industrial and Manufacturing Engineering 25
  • Emergency Medicine 21
  • Geometry and Topology 20
  • Artificial Intelligence 20
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Citations per field, relative to Zbigniew Leś
Zbigniew Leś · 1×
Citations per year, relative to Zbigniew Leś
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Countries citing papers authored by Zbigniew Leś

Since Specialization
Citations

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

Fields of papers citing papers by Zbigniew Leś

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Zbigniew Leś

This figure shows the co-authorship network connecting the top 25 collaborators of Zbigniew Leś. A scholar is included among the top collaborators of Zbigniew Leś 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 Zbigniew Leś. Zbigniew Leś 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
# Work Indexed citations
1 8
2 9
3 24
4
Machine Understanding - a new area of research aimed at building thinking/understanding machines
1
5 1
6 0
7
Shape understanding system the first steps toward the visual thinking machines
6
8 3
9 0
10 3
11 4
12 3
13 5
14
Shape Understanding System: The Noisy Class
4
15
Shape Understanding System: Learning of the Visual Concepts
8
16 3
17 16
18 16
19
System of experts to perform an epistemological task of shape understanding
14
20
Shape understanding system in automotive and transportation technology
5

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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