Maria Trocan

1.0k citations
73 papers · 516 indexed · h-index 13
Topics
Image and Signal Denoising Methods (25 papers)Advanced Image Processing Techniques (21 papers)Sparse and Compressive Sensing Techniques (18 papers)
Partner nations
FranceChinaUnited States

In The Last Decade

Maria Trocan

66 papers receiving 506 citations

Peers

Maria Trocan
Comparison fields: 5 of 94
  • Computer Vision and Pattern Recognition 232
  • Computational Mechanics 109
  • Media Technology 95
  • Artificial Intelligence 77
  • Signal Processing 71
Replace Stefan A. Robila with:
Stefan A. Robila United States
Xingsong Hou China
Li Guo China
Ke-Kun Huang China
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Sanjiv Kumar United States
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Maria Trocan relative to Stefan A. Robila United States Stefan A. Robila's profile →
Citations per field
00.5×6.1×
Stefan A. Robila · 1×
Citations per year

Countries citing papers authored by Maria Trocan

Since Specialization
Citations

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

Fields of papers citing papers by Maria Trocan

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Maria Trocan

This figure shows the co-authorship network connecting the top 25 collaborators of Maria Trocan. A scholar is included among the top collaborators of Maria Trocan 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 Maria Trocan. Maria Trocan 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 5
3 29
4 1
5 8
6 20
7 3
8 16
9 17
10 5
11 9
12 8
13 1
14
Smooth motion-compensated video deinterlacing
3
15 1
16
CS-reconstruction of multiview images using bootstrap-like disparity compensation
1
17 5
18 0
19 1
20 4

About Maria Trocan

Maria Trocan is a scholar working on Computer Vision and Pattern Recognition, Media Technology and Signal Processing, having authored 73 papers that have together received 516 indexed citations. Recurring topics across this work include Image and Signal Denoising Methods (25 papers), Advanced Image Processing Techniques (21 papers) and Sparse and Compressive Sensing Techniques (18 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (232 citations), Media Technology (95 citations) and Signal Processing (71 citations). Maria Trocan has collaborated with scholars based in France, China and United States. Frequent co-authors include Ali Akbari, Honggui Li, James E. Fowler, Jérémie Sublime, Béatrice Pesquet‐Popescu, Shohreh Ahvar, Bertrand Granado, Thomas Maugey, Eric W. Tramel and Dino Ienco. Their work appears in journals such as IEEE Communications Magazine, Sensors and ACM Computing Surveys.

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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