Daochang Liu

30 total papers · 654 total citations
11 papers, 264 citations indexed

About

Daochang Liu is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Biomedical Engineering. According to data from OpenAlex, Daochang Liu has authored 11 papers receiving a total of 264 indexed citations (citations by other indexed papers that have themselves been cited), including 7 papers in Computer Vision and Pattern Recognition, 3 papers in Artificial Intelligence and 3 papers in Biomedical Engineering. Recurrent topics in Daochang Liu's work include Human Pose and Action Recognition (3 papers), Generative Adversarial Networks and Image Synthesis (2 papers) and Surgical Simulation and Training (2 papers). Daochang Liu is often cited by papers focused on Human Pose and Action Recognition (3 papers), Generative Adversarial Networks and Image Synthesis (2 papers) and Surgical Simulation and Training (2 papers). Daochang Liu collaborates with scholars based in China, Australia and United States. Daochang Liu's co-authors include Tingting Jiang, Yizhou Wang, Fei Shan, Ziyu Li, Rulin Miao, Chang Xu, Mubarak Shah, Tingting Jiang, Qiyue Li and Jianlong Fu and has published in prestigious journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence and International Journal of Computer Assisted Radiology and Surgery.

In The Last Decade

Daochang Liu

10 papers receiving 259 citations

Author Peers

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

Author						Papers	Cites
Daochang Liu	213	139	56	28	18	11	264
Xinpeng Ding	214 1.0×	88 0.6×	49 0.9×	40 1.4×	3 0.2×	19	326
Yiming Hao	198 0.9×	80 0.6×	16 0.3×	5 0.2×	5 0.3×	9	314
Aaron Jaech	66 0.3×	99 0.7×	55 1.0×	7 0.3×	7 0.4×	15	209
Yi Li	197 0.9×	46 0.3×	34 0.6×	11 0.4×	3 0.2×	12	316
Connah Kendrick	127 0.6×	118 0.8×	22 0.4×	3 0.1×	22 1.2×	17	307
Manfred Georg	93 0.4×	40 0.3×	32 0.6×	9 0.3×	5 0.3×	12	209
Cédric Penet	121 0.6×	87 0.6×	46 0.8×	46 1.6×		6	185
Tianpeng Li	166 0.8×	83 0.6×	26 0.5×	35 1.3×	12 0.7×	9	302
Preksha Pareek	208 1.0×	152 1.1×	67 1.2×	4 0.1×	2 0.1×	11	305
Yu-Siang Wang	135 0.6×	161 1.2×	21 0.4×	9 0.3×		10	276

Countries citing papers authored by Daochang Liu

Since Specialization

Citations

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

Fields of papers citing papers by Daochang Liu

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Daochang Liu

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