L.M. Cheng

196 total papers · 4.5k total citations
127 papers, 3.3k citations indexed

About

L.M. Cheng is a scholar working on Computer Vision and Pattern Recognition, Electrical and Electronic Engineering and Artificial Intelligence. According to data from OpenAlex, L.M. Cheng has authored 127 papers receiving a total of 3.3k indexed citations (citations by other indexed papers that have themselves been cited), including 46 papers in Computer Vision and Pattern Recognition, 33 papers in Electrical and Electronic Engineering and 28 papers in Artificial Intelligence. Recurrent topics in L.M. Cheng's work include Chaos-based Image/Signal Encryption (29 papers), Advanced Steganography and Watermarking Techniques (25 papers) and Digital Media Forensic Detection (18 papers). L.M. Cheng is often cited by papers focused on Chaos-based Image/Signal Encryption (29 papers), Advanced Steganography and Watermarking Techniques (25 papers) and Digital Media Forensic Detection (18 papers). L.M. Cheng collaborates with scholars based in Hong Kong, United States and China. L.M. Cheng's co-authors include Chi-Kwong Chan, Edward G. Lakatta, Rebecca Pauly, Robert E. Monticone, Bertram Sacktor, Jeffrey P. Froehlich, Michael T. Crow, L. L. Cheng, Antonino Passaniti and C. T. Liang and has published in prestigious journals such as Journal of Biological Chemistry, Journal of Clinical Investigation and Circulation Research.

In The Last Decade

L.M. Cheng

117 papers receiving 3.0k citations

Hit Papers

Hiding data in images by ... 2003 2026 2010 2018 2003 250 500 750 1000

Author Peers

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

Author Last Decade Papers Cites
L.M. Cheng 1.7k 428 378 345 321 127 3.3k
Yongmin Li 1.2k 0.7× 708 1.7× 220 0.6× 154 0.4× 497 1.5× 154 3.7k
Ziming Zhang 1.3k 0.8× 797 1.9× 232 0.6× 166 0.5× 89 0.3× 202 3.7k
Zitao Liu 1.1k 0.7× 427 1.0× 145 0.4× 367 1.1× 129 0.4× 143 3.2k
Sudipta Roy 628 0.4× 344 0.8× 141 0.4× 119 0.3× 214 0.7× 146 2.7k
Shai Fine 484 0.3× 955 2.2× 108 0.3× 210 0.6× 255 0.8× 101 6.7k
Hongmin Cai 778 0.5× 393 0.9× 295 0.8× 203 0.6× 89 0.3× 199 2.9k
Tahsin Kurç 1.1k 0.7× 617 1.4× 1.3k 3.5× 538 1.6× 357 1.1× 220 4.9k
Wenyuan Yu 302 0.2× 596 1.4× 297 0.8× 312 0.9× 54 0.2× 150 3.1k
Bing Zeng 4.1k 2.4× 437 1.0× 423 1.1× 112 0.3× 367 1.1× 351 6.7k
Lin Yang 1.4k 0.8× 478 1.1× 182 0.5× 114 0.3× 49 0.2× 119 2.8k

Countries citing papers authored by L.M. Cheng

Since Specialization
Citations

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

Fields of papers citing papers by L.M. Cheng

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by L.M. Cheng. 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 L.M. Cheng. The network helps show where L.M. Cheng may publish in the future.

Co-authorship network of co-authors of L.M. Cheng

This figure shows the co-authorship network connecting the top 25 collaborators of L.M. Cheng. A scholar is included among the top collaborators of L.M. Cheng 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 L.M. Cheng. L.M. Cheng 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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