Lidan Shou

164 total papers · 1.8k total citations
110 papers, 1.1k citations indexed

About

Lidan Shou is a scholar working on Signal Processing, Artificial Intelligence and Computer Vision and Pattern Recognition. According to data from OpenAlex, Lidan Shou has authored 110 papers receiving a total of 1.1k indexed citations (citations by other indexed papers that have themselves been cited), including 49 papers in Signal Processing, 39 papers in Artificial Intelligence and 35 papers in Computer Vision and Pattern Recognition. Recurrent topics in Lidan Shou's work include Data Management and Algorithms (41 papers), Advanced Image and Video Retrieval Techniques (16 papers) and Advanced Database Systems and Queries (14 papers). Lidan Shou is often cited by papers focused on Data Management and Algorithms (41 papers), Advanced Image and Video Retrieval Techniques (16 papers) and Advanced Database Systems and Queries (14 papers). Lidan Shou collaborates with scholars based in China, Denmark and Singapore. Lidan Shou's co-authors include Gang Chen, Ke Chen, Hua Lu, Ke Chen, Jue Wang, Huan Li, Zhenhua Wang, Kian‐Lee Tan, Jiajun Lu and Thomas La Porta and has published in prestigious journals such as Scientific Reports, Expert Systems with Applications and IEEE Access.

In The Last Decade

Lidan Shou

101 papers receiving 1.1k citations

Author Peers

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

Author Last Decade Papers Cites
Lidan Shou 472 323 271 258 225 110 1.1k
Lei Zhao 681 1.4× 250 0.8× 411 1.5× 280 1.1× 275 1.2× 155 1.3k
Xike Xie 305 0.6× 389 1.2× 143 0.5× 301 1.2× 150 0.7× 74 1.0k
Bolong Zheng 584 1.2× 587 1.8× 413 1.5× 335 1.3× 245 1.1× 87 1.5k
An Liu 673 1.4× 201 0.6× 532 2.0× 479 1.9× 158 0.7× 130 1.4k
Xiaochun Yang 650 1.4× 343 1.1× 301 1.1× 299 1.2× 232 1.0× 130 1.2k
Fengli Zhang 553 1.2× 245 0.8× 251 0.9× 292 1.1× 125 0.6× 130 1.4k
Da Yan 594 1.3× 355 1.1× 491 1.8× 385 1.5× 770 3.4× 108 1.5k
Wei Wu 449 1.0× 216 0.7× 377 1.4× 308 1.2× 155 0.7× 75 930
Xingjie Liu 250 0.5× 155 0.5× 395 1.5× 233 0.9× 87 0.4× 58 981
Chaokun Wang 604 1.3× 187 0.6× 450 1.7× 374 1.4× 267 1.2× 116 1.3k

Countries citing papers authored by Lidan Shou

Since Specialization
Citations

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

Fields of papers citing papers by Lidan Shou

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Lidan Shou

This figure shows the co-authorship network connecting the top 25 collaborators of Lidan Shou. A scholar is included among the top collaborators of Lidan Shou 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 Lidan Shou. Lidan Shou 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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