Min Cao

67 total papers · 666 total citations
40 papers, 482 citations indexed

About

Min Cao is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Materials Chemistry. According to data from OpenAlex, Min Cao has authored 40 papers receiving a total of 482 indexed citations (citations by other indexed papers that have themselves been cited), including 17 papers in Computer Vision and Pattern Recognition, 8 papers in Artificial Intelligence and 6 papers in Materials Chemistry. Recurrent topics in Min Cao's work include Video Surveillance and Tracking Methods (11 papers), Multimodal Machine Learning Applications (6 papers) and Human Pose and Action Recognition (6 papers). Min Cao is often cited by papers focused on Video Surveillance and Tracking Methods (11 papers), Multimodal Machine Learning Applications (6 papers) and Human Pose and Action Recognition (6 papers). Min Cao collaborates with scholars based in China, Hong Kong and Nigeria. Min Cao's co-authors include Fuhui Wang, Li Liu, Lei Fan, Ying Li, Min Zhang, Shiping Li, Yuyu Yin, Kaili Xu, Honghao Gao and Qiang Xu and has published in prestigious journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, Scientific Reports and Corrosion Science.

In The Last Decade

Min Cao

30 papers receiving 466 citations

Author Peers

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

Author						Papers	Cites
Min Cao	177	140	118	84	62	40	482
Xiaoyu Yang	213 1.2×	229 1.6×	144 1.2×	114 1.4×	80 1.3×	52	522
Zixi Jia	128 0.7×	76 0.5×	52 0.4×	61 0.7×	54 0.9×	45	490
Tang Bo	55 0.3×	204 1.5×	11 0.1×	31 0.4×	54 0.9×	16	416
Vinay Kumar Verma	53 0.3×	68 0.5×	213 1.8×	15 0.2×	46 0.7×	42	470
Parijat Deshpande	104 0.6×	99 0.7×	18 0.2×	24 0.3×	59 1.0×	30	427
Pu Xie	58 0.3×	173 1.2×	50 0.4×	81 1.0×	39 0.6×	39	412
Oh‐Heum Kwon	194 1.1×	260 1.9×	86 0.7×	64 0.8×	175 2.8×	34	510
Claudia Rinaldi	114 0.6×	168 1.2×	39 0.3×	101 1.2×	96 1.5×	54	473
Ke Ma	81 0.5×	176 1.3×	71 0.6×	76 0.9×	19 0.3×	43	421
Patrick T. Brewick	67 0.4×	112 0.8×	26 0.2×	57 0.7×	57 0.9×	40	417

Countries citing papers authored by Min Cao

Since Specialization

Citations

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

Fields of papers citing papers by Min Cao

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Min Cao

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