T. P. Trzcinski

10.7k citations
62 papers · 1.3k indexed · 1 hit paper · h-index 13
Topics
Domain Adaptation and Few-Shot Learning (12 papers)Advanced Image and Video Retrieval Techniques (11 papers)Terahertz technology and applications (8 papers)
Partner nations
PolandSwitzerlandSpain

In The Last Decade

T. P. Trzcinski

53 papers receiving 1.2k citations

Hit Papers

BRIEF: Computing a Local Binary Descriptor Very Fast20112026201620212011100200300400500

Peers

T. P. Trzcinski
Comparison fields: 5 of 97
  • Computer Vision and Pattern Recognition 942
  • Aerospace Engineering 538
  • Artificial Intelligence 140
  • Media Technology 121
  • Electrical and Electronic Engineering 121
Replace Haotian Tang with:
Haotian Tang United States
Jinming Duan United Kingdom
Richard Souvenir United States
N. Nandhakumar United States
Rama Krishna Gorthi India
Umme Sara Bangladesh
Reg G. Willson United States
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Mark Thurston United Kingdom
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T. P. Trzcinski relative to Haotian Tang United States Haotian Tang's profile →
Citations per field
00.5×4.5×
Haotian Tang · 1×
Citations per year

Countries citing papers authored by T. P. Trzcinski

Since Specialization
Citations

This map shows the geographic impact of T. P. Trzcinski'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 T. P. Trzcinski with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites T. P. Trzcinski more than expected).

Fields of papers citing papers by T. P. Trzcinski

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by T. P. Trzcinski. 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 T. P. Trzcinski. The network helps show where T. P. Trzcinski may publish in the future.

Co-authorship network of co-authors of T. P. Trzcinski

This figure shows the co-authorship network connecting the top 25 collaborators of T. P. Trzcinski. A scholar is included among the top collaborators of T. P. Trzcinski 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 T. P. Trzcinski. T. P. Trzcinski 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 0
2 3
3 6
4 4
5 2
6 5
7 6
8 6
9 1
10 3
11 28
12 4
13 28
14
End-to-end Sinkhorn Autoencoder with noise generator
5
15 9
16
BinGAN: Learning Compact Binary Descriptors with a Regularized GAN
21
17 1
18
Learning Image Descriptors with the Boosting-Trick
54
19
BRIEF: Computing a Local Binary Descriptor Very Fastbreakdown →
569
20 2

About T. P. Trzcinski

T. P. Trzcinski is a scholar working on Computer Vision and Pattern Recognition, Computer Graphics and Computer-Aided Design and Artificial Intelligence, having authored 62 papers that have together received 1.3k indexed citations. Recurring topics across this work include Domain Adaptation and Few-Shot Learning (12 papers), Advanced Image and Video Retrieval Techniques (11 papers) and Terahertz technology and applications (8 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (942 citations), Aerospace Engineering (538 citations) and Media Technology (121 citations). T. P. Trzcinski has collaborated with scholars based in Poland, Switzerland and Spain. Frequent co-authors include Vincent Lepetit, Pascal Fua, Christoph Strecha, Michael Calonder, Mustafa Özuysal, Mario Christoudias, Norbert Pałka, M. Szustakowski, Qingqun Kong and Zhiheng Wang. Their work appears in journals such as SHILAP Revista de lepidopterología, IEEE Transactions on Pattern Analysis and Machine Intelligence and IEEE Transactions on Image Processing.

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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