Junyu Gao

115 total papers · 4.0k total citations
69 papers, 1.5k citations indexed

About

Junyu Gao is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Biomedical Engineering. According to data from OpenAlex, Junyu Gao has authored 69 papers receiving a total of 1.5k indexed citations (citations by other indexed papers that have themselves been cited), including 52 papers in Computer Vision and Pattern Recognition, 32 papers in Artificial Intelligence and 7 papers in Biomedical Engineering. Recurrent topics in Junyu Gao's work include Human Pose and Action Recognition (36 papers), Multimodal Machine Learning Applications (27 papers) and Anomaly Detection Techniques and Applications (16 papers). Junyu Gao is often cited by papers focused on Human Pose and Action Recognition (36 papers), Multimodal Machine Learning Applications (27 papers) and Anomaly Detection Techniques and Applications (16 papers). Junyu Gao collaborates with scholars based in China, United States and Hong Kong. Junyu Gao's co-authors include Changsheng Xu, Tianzhu Zhang, Xiaoshan Yang, Mengyuan Chen, Dai Wang, Jianfeng Dong, Pan Li, Bin Fan, Samveg Saxena and Bin Wang and has published in prestigious journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, Journal of Power Sources and IEEE Transactions on Image Processing.

In The Last Decade

Junyu Gao

57 papers receiving 1.4k citations

Hit Papers

I Know the Relationships:... 2019 2026 2021 2023 2019 40 80 120

Author Peers

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

Author Last Decade Papers Cites
Junyu Gao 1.2k 564 136 130 97 69 1.5k
Ming‐Ching Chang 1.2k 1.0× 498 0.9× 113 0.8× 72 0.6× 74 0.8× 106 1.7k
Yuan Li 610 0.5× 366 0.6× 80 0.6× 156 1.2× 80 0.8× 67 1.1k
Jiale Cao 1.2k 1.0× 308 0.5× 67 0.5× 95 0.7× 91 0.9× 73 1.6k
Jianhua Zou 567 0.5× 329 0.6× 68 0.5× 174 1.3× 59 0.6× 58 1.2k
Liyan Zhang 1.2k 1.0× 564 1.0× 216 1.6× 113 0.9× 26 0.3× 92 1.8k
Neil M. Robertson 1.1k 0.9× 453 0.8× 145 1.1× 91 0.7× 34 0.4× 81 1.5k
Jianwu Fang 711 0.6× 352 0.6× 47 0.3× 56 0.4× 253 2.6× 77 1.1k
Yuntao Chen 1.2k 1.0× 322 0.6× 116 0.9× 133 1.0× 86 0.9× 50 1.8k
Soon Ki Jung 1.0k 0.9× 178 0.3× 73 0.5× 87 0.7× 56 0.6× 106 1.5k
Hsu-Yung Cheng 709 0.6× 419 0.7× 69 0.5× 294 2.3× 368 3.8× 81 1.4k

Countries citing papers authored by Junyu Gao

Since Specialization
Citations

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

Fields of papers citing papers by Junyu Gao

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Junyu Gao

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