Linjun Zhou

444 total citations
7 papers, 239 citations indexed

About

Linjun Zhou is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Radiology, Nuclear Medicine and Imaging. According to data from OpenAlex, Linjun Zhou has authored 7 papers receiving a total of 239 indexed citations (citations by other indexed papers that have themselves been cited), including 7 papers in Artificial Intelligence, 5 papers in Computer Vision and Pattern Recognition and 1 paper in Radiology, Nuclear Medicine and Imaging. Recurrent topics in Linjun Zhou's work include Domain Adaptation and Few-Shot Learning (7 papers), Multimodal Machine Learning Applications (3 papers) and Adversarial Robustness in Machine Learning (2 papers). Linjun Zhou is often cited by papers focused on Domain Adaptation and Few-Shot Learning (7 papers), Multimodal Machine Learning Applications (3 papers) and Adversarial Robustness in Machine Learning (2 papers). Linjun Zhou collaborates with scholars based in China and Sweden. Linjun Zhou's co-authors include Peng Cui, Zheyan Shen, Xingxuan Zhang, Renzhe Xu, Yue He, Qi Tian, Shiqiang Yang, Xu Jia, Jiashuo Liu and Kun Kuang and has published in prestigious journals such as IEEE Transactions on Knowledge and Data Engineering, 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) and Proceedings of the AAAI Conference on Artificial Intelligence.

In The Last Decade

Linjun Zhou

7 papers receiving 233 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name	h						Papers	Cites
Linjun Zhou China	6	170	101	15	14	13	7	239
Xingxuan Zhang China	7	175 1.0×	108 1.1×	17 1.1×	15 1.1×	11 0.8×	12	263
Renzhe Xu China	7	181 1.1×	105 1.0×	18 1.2×	14 1.0×	12 0.9×	17	276
Jaemin Na South Korea	3	152 0.9×	127 1.3×	11 0.7×	13 0.9×	16 1.2×	7	216
Ricardo Sousa Portugal	8	109 0.6×	50 0.5×	15 1.0×	8 0.6×	4 0.3×	23	191
Nan Song China	5	182 1.1×	114 1.1×	12 0.8×	14 1.0×	29 2.2×	15	263
Kaixiong Gong China	5	212 1.2×	157 1.6×	10 0.7×	12 0.9×	27 2.1×	11	277
Xinzhe Li China	7	140 0.8×	114 1.1×	7 0.5×	8 0.6×	21 1.6×	20	203
Tong Che Algeria	7	199 1.2×	140 1.4×	12 0.8×	10 0.7×	42 3.2×	9	268
Shunfeng Zhou China	4	216 1.3×	270 2.7×	12 0.8×	15 1.1×	17 1.3×	6	392

Countries citing papers authored by Linjun Zhou

Since Specialization

Citations

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

Fields of papers citing papers by Linjun Zhou

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Linjun Zhou

This figure shows the co-authorship network connecting the top 25 collaborators of Linjun Zhou. A scholar is included among the top collaborators of Linjun Zhou 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 Linjun Zhou. Linjun Zhou is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

Sort: Min cites: Since: Top N: Style:

7 of 7 papers shown

1.

Zhang, Xingxuan, et al.. (2022). Towards Unsupervised Domain Generalization. 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR). 4900–4910. 24 indexed citations

2.

Zhou, Linjun, Peng Cui, Xingxuan Zhang, Yinan Jiang, & Shiqiang Yang. (2022). Adversarial Eigen Attack on BlackBox Models. 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR). 15233–15241. 9 indexed citations

3.

Liu, Jiashuo, Zheyan Shen, Peng Cui, et al.. (2022). Distributionally Robust Learning With Stable Adversarial Training. IEEE Transactions on Knowledge and Data Engineering. 35(11). 11288–11300. 4 indexed citations

4.

Liu, Jiashuo, Zheyan Shen, Peng Cui, et al.. (2021). Stable Adversarial Learning under Distributional Shifts. Proceedings of the AAAI Conference on Artificial Intelligence. 35(10). 8662–8670. 13 indexed citations

5.

Zhang, Xingxuan, Peng Cui, Renzhe Xu, et al.. (2021). Deep Stable Learning for Out-Of-Distribution Generalization. 5368–5378. 163 indexed citations

6.

Zhou, Linjun, Peng Cui, Xu Jia, Shiqiang Yang, & Qi Tian. (2020). Learning to Select Base Classes for Few-Shot Classification. 4623–4632. 15 indexed citations

7.

Zhou, Linjun, Peng Cui, Shiqiang Yang, Wenwu Zhu, & Qi Tian. (2019). Learning to Learn Image Classifiers With Visual Analogy. 11489–11498. 11 indexed citations

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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