He Cheng

33 total papers · 730 total citations
20 papers, 544 citations indexed

About

He Cheng is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Computer Networks and Communications. According to data from OpenAlex, He Cheng has authored 20 papers receiving a total of 544 indexed citations (citations by other indexed papers that have themselves been cited), including 9 papers in Artificial Intelligence, 7 papers in Computer Vision and Pattern Recognition and 5 papers in Computer Networks and Communications. Recurrent topics in He Cheng's work include AI in cancer detection (4 papers), Radiomics and Machine Learning in Medical Imaging (4 papers) and Anomaly Detection Techniques and Applications (4 papers). He Cheng is often cited by papers focused on AI in cancer detection (4 papers), Radiomics and Machine Learning in Medical Imaging (4 papers) and Anomaly Detection Techniques and Applications (4 papers). He Cheng collaborates with scholars based in United States, China and Canada. He Cheng's co-authors include Ji‐Guang Li, Yingtao Zhang, Boyu Zhang, Min Xian, Xiangjun Shi, Fei Xu, Jianrui Ding, Jingli Wang, Xue Mei and Ping Xing and has published in prestigious journals such as Pattern Recognition, Information Sciences and Neurocomputing.

In The Last Decade

He Cheng

18 papers receiving 510 citations

Author Peers

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

Author						Papers	Cites
He Cheng	348	272	182	116	50	20	544
Farhan Akram	224 0.6×	244 0.9×	147 0.8×	58 0.5×	33 0.7×	31	494
Lazaros Tsochatzidis	256 0.7×	257 0.9×	183 1.0×	47 0.4×	65 1.3×	14	506
Yutong Bai	382 1.1×	225 0.8×	83 0.5×	68 0.6×	23 0.5×	19	604
Junqian Wang	335 1.0×	217 0.8×	91 0.5×	126 1.1×	28 0.6×	16	522
Shaveta Arora	288 0.8×	105 0.4×	110 0.6×	118 1.0×	50 1.0×	30	455
Shibaprasad Sen	173 0.5×	254 0.9×	166 0.9×	62 0.5×	32 0.6×	28	499
Fátima N. S. de Medeiros	202 0.6×	208 0.8×	183 1.0×	33 0.3×	29 0.6×	23	499
K. Balasamy	263 0.8×	159 0.6×	174 1.0×	35 0.3×	93 1.9×	19	595
Annapurna Singh	402 1.2×	276 1.0×	153 0.8×	57 0.5×	54 1.1×	34	588
Yawen Huang	334 1.0×	131 0.5×	114 0.6×	109 0.9×	33 0.7×	49	493

Countries citing papers authored by He Cheng

Since Specialization

Citations

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

Fields of papers citing papers by He Cheng

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of He Cheng

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