Dakun Zhang

109 total papers · 827 total citations
52 papers, 509 citations indexed

About

Dakun Zhang is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Electrical and Electronic Engineering. According to data from OpenAlex, Dakun Zhang has authored 52 papers receiving a total of 509 indexed citations (citations by other indexed papers that have themselves been cited), including 17 papers in Computer Vision and Pattern Recognition, 11 papers in Artificial Intelligence and 10 papers in Electrical and Electronic Engineering. Recurrent topics in Dakun Zhang's work include Topic Modeling (10 papers), Natural Language Processing Techniques (9 papers) and Interconnection Networks and Systems (7 papers). Dakun Zhang is often cited by papers focused on Topic Modeling (10 papers), Natural Language Processing Techniques (9 papers) and Interconnection Networks and Systems (7 papers). Dakun Zhang collaborates with scholars based in China, United States and Japan. Dakun Zhang's co-authors include Qin Shu, Ping Liang, Yongyan Gao, Xiaoling Yu, Yang Wang, Liping Liu, Min Chen, Ruifang Wang, Jean Sénellart and Cui Huang and has published in prestigious journals such as SHILAP Revista de lepidopterología, The Journal of Urology and IEEE Access.

In The Last Decade

Dakun Zhang

47 papers receiving 490 citations

Author Peers

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

Author						Papers	Cites
Dakun Zhang	102	90	85	76	74	52	509
Haowen Tang	26 0.3×	136 1.5×	31 0.4×	122 1.6×	70 0.9×	58	607
Yifan Wang	55 0.5×	65 0.7×	19 0.2×	60 0.8×	27 0.4×	60	540
Zhe Guo	57 0.6×	54 0.6×	131 1.5×	47 0.6×	24 0.3×	36	567
Lucian Gheorghe Gruionu	26 0.3×	115 1.3×	41 0.5×	27 0.4×	36 0.5×	53	526
Feng Chen	19 0.2×	43 0.5×	31 0.4×	100 1.3×	53 0.7×	44	555
Rusi Chen	193 1.9×	36 0.4×	110 1.3×	35 0.5×	25 0.3×	59	546
Xiaoyong Wang	67 0.7×	71 0.8×	17 0.2×	62 0.8×	93 1.3×	65	576
Matsuda	150 1.5×	122 1.4×	10 0.1×	70 0.9×	29 0.4×	56	556
Jiawei Liang	64 0.6×	50 0.6×	94 1.1×	60 0.8×	27 0.4×	67	553
Jared O’Leary	49 0.5×	147 1.6×	13 0.2×	23 0.3×	111 1.5×	31	548

Countries citing papers authored by Dakun Zhang

Since Specialization

Citations

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

Fields of papers citing papers by Dakun Zhang

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Dakun Zhang

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