Michel Sarkis

45 total papers · 488 total citations
26 papers, 300 citations indexed

About

Michel Sarkis is a scholar working on Computer Vision and Pattern Recognition, Computational Mechanics and Media Technology. According to data from OpenAlex, Michel Sarkis has authored 26 papers receiving a total of 300 indexed citations (citations by other indexed papers that have themselves been cited), including 23 papers in Computer Vision and Pattern Recognition, 7 papers in Computational Mechanics and 7 papers in Media Technology. Recurrent topics in Michel Sarkis's work include Advanced Vision and Imaging (13 papers), Optical measurement and interference techniques (7 papers) and Image Processing Techniques and Applications (6 papers). Michel Sarkis is often cited by papers focused on Advanced Vision and Imaging (13 papers), Optical measurement and interference techniques (7 papers) and Image Processing Techniques and Applications (6 papers). Michel Sarkis collaborates with scholars based in Germany, United States and United Kingdom. Michel Sarkis's co-authors include Shang‐Hong Lai, Klaus Diepold, Xiaoming Liu, Yiying Tong, Knut Hüper, Ruofeng Tong, Guoyu Lu, Yawen Lu, Ravi Ramamoorthi and Min Tang and has published in prestigious journals such as IEEE Transactions on Image Processing, IEEE Transactions on Visualization and Computer Graphics and 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).

In The Last Decade

Michel Sarkis

23 papers receiving 287 citations

Author Peers

Peers are selected by citation overlap in the author's most active subfields. citations · hero ref

Author						Papers	Cites
Michel Sarkis	258	93	44	34	33	26	300
Shandong Wang	188 0.7×	151 1.6×	13 0.3×	21 0.6×	30 0.9×	27	278
Shuyang Wang	222 0.9×	28 0.3×	22 0.5×	6 0.2×	28 0.8×	25	321
Jinhee Chun	156 0.6×	95 1.0×	11 0.3×	34 1.0×	8 0.2×	19	233
Huan Wang	155 0.6×	8 0.1×	24 0.5×	20 0.6×	32 1.0×	27	220
Douglas Fidaleo	228 0.9×	19 0.2×	57 1.3×	10 0.3×	7 0.2×	18	330
Bernhard Egger	231 0.9×	17 0.2×	63 1.4×	18 0.5×	5 0.2×	28	337
Yezhi Shu	180 0.7×	51 0.5×	5 0.1×	13 0.4×	42 1.3×	14	257
Charles Herrmann	168 0.7×	12 0.1×	9 0.2×	30 0.9×	21 0.6×	22	277
Peng Liu	227 0.9×	96 1.0×	14 0.3×	2 0.1×	60 1.8×	20	334
Sunok Kim	242 0.9×	73 0.8×	4 0.1×	6 0.2×	73 2.2×	35	301

Countries citing papers authored by Michel Sarkis

Since Specialization

Citations

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

Fields of papers citing papers by Michel Sarkis

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Michel Sarkis

This figure shows the co-authorship network connecting the top 25 collaborators of Michel Sarkis. A scholar is included among the top collaborators of Michel Sarkis 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 Michel Sarkis. Michel Sarkis is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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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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