Jun Shi

2.0k total citations · 1 hit paper
66 papers, 1.4k citations indexed

About

Jun Shi is a scholar working on Aerospace Engineering, Computer Vision and Pattern Recognition and Computational Mechanics. According to data from OpenAlex, Jun Shi has authored 66 papers receiving a total of 1.4k indexed citations (citations by other indexed papers that have themselves been cited), including 29 papers in Aerospace Engineering, 17 papers in Computer Vision and Pattern Recognition and 13 papers in Computational Mechanics. Recurrent topics in Jun Shi's work include Advanced SAR Imaging Techniques (21 papers), Synthetic Aperture Radar (SAR) Applications and Techniques (12 papers) and Microwave Imaging and Scattering Analysis (12 papers). Jun Shi is often cited by papers focused on Advanced SAR Imaging Techniques (21 papers), Synthetic Aperture Radar (SAR) Applications and Techniques (12 papers) and Microwave Imaging and Scattering Analysis (12 papers). Jun Shi collaborates with scholars based in China, Canada and United States. Jun Shi's co-authors include Shunjun Wei, Mou Wang, Qizhe Qu, Hao Su, Xiangfeng Zeng, Xiaoling Zhang, Longgang Hou, Wangtu Huo, J.S. Zhang and Yue Wu and has published in prestigious journals such as SHILAP Revista de lepidopterología, Chemosphere and IEEE Access.

In The Last Decade

Jun Shi

61 papers receiving 1.4k citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

HRSID: A High-Resolution SAR Images Dataset for Ship Detection and Instance Segmentation

2020 562 citations Shunjun Wei, Xiangfeng Zeng et al. profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Jun Shi China	16	844	477	243	221	180	66	1.4k
Bin Zou China	22	784 0.9×	220 0.5×	97 0.4×	64 0.3×	152 0.8×	165	1.8k
Jiaming Sun China	12	682 0.8×	1.3k 2.7×	59 0.2×	179 0.8×	52 0.3×	44	1.7k
Jin Zhao China	22	390 0.5×	484 1.0×	61 0.3×	38 0.2×	110 0.6×	74	1.6k
Miao Kang China	10	578 0.7×	452 0.9×	80 0.3×	40 0.2×	212 1.2×	21	971
Hao Su China	17	1.5k 1.8×	1.3k 2.8×	52 0.2×	65 0.3×	331 1.8×	39	2.3k
Gerard Dooly Ireland	20	412 0.5×	395 0.8×	222 0.9×	41 0.2×	578 3.2×	121	1.7k
Hongjian Wang China	19	329 0.4×	442 0.9×	61 0.3×	25 0.1×	424 2.4×	133	1.2k

Countries citing papers authored by Jun Shi

Since Specialization

Citations

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

Fields of papers citing papers by Jun Shi

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Jun Shi

This figure shows the co-authorship network connecting the top 25 collaborators of Jun Shi. A scholar is included among the top collaborators of Jun Shi 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 Jun Shi. Jun Shi 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:

20 of 20 papers shown

1.

Yang, Wenxiao, Dan Lin, Hui Mu, et al.. (2025). Effectiveness of Shuanghuang Yangxue Decoction for Treating Cancer-Related Anemia With Serum Iron Deficiency in Lung Cancer Patients: A Randomized Clinical Trial. Integrative Cancer Therapies. 24. 1583711178–1583711178.

2.

Wei, Shunjun, et al.. (2024). CMTI: Non-Line-of-Sight Radar Imaging for Non-Cooperative Corner Motion Target. IEEE Transactions on Vehicular Technology. 74(1). 179–190. 7 indexed citations

3.

Zhang, Xiaoling, Yu Ren, Xu Zhan, et al.. (2023). Tomographic Imaging with Enhanced Spatial Structures Via a Physics-Aware 3D Reconstruction Network. 1922–1925. 1 indexed citations

4.

Zhang, Min, Jun Shi, & Huiping Deng. (2023). Transcriptome-wide m6A modification mediates cardiotoxicity in mice after chronic exposure to microplastics. Chemosphere. 317. 137877–137877. 18 indexed citations

5.

Zhang, Min, Jun Shi, Jun Zhou, et al.. (2023). N6-methyladenosine methylation mediates non-coding RNAs modification in microplastic-induced cardiac injury. Ecotoxicology and Environmental Safety. 262. 115174–115174. 16 indexed citations

6.

Wei, Shunjun, et al.. (2023). O-Unet: An Octree-Based Convolutional Neural Network for 3-D Radar Point Clouds Reconstruction. 4419–4422. 2 indexed citations

7.

Zhang, Xiaoling, et al.. (2021). Fast Bayesian Compressed Sensing Algorithm via Relevance Vector Machine for LASAR 3D Imaging. Remote Sensing. 13(9). 1751–1751. 11 indexed citations

8.

Wei, Shunjun, et al.. (2021). Non-Line-Of-Sight Imaging by Millimeter Wave Radar. 2983–2986. 9 indexed citations

9.

Shi, Jun, Linlin Wang, Shanshan Wang, et al.. (2020). Applications of deep learning in medical imaging: a survey. Journal of Image and Graphics. 25(10). 1953–1981. 8 indexed citations

10.

Wei, Shunjun, Jiadian Liang, Mou Wang, et al.. (2020). CIST: An Improved ISAR Imaging Method Using Convolution Neural Network. Remote Sensing. 12(16). 2641–2641. 34 indexed citations

11.

Zhang, Xiaoling, et al.. (2019). High-speed and High-accurate SAR Ship Detection Based on a Depthwise Separable Convolution Neural Network. SHILAP Revista de lepidopterología. 20 indexed citations

12.

Ling, Peter P., et al.. (2018). PSF Analysis and Ground Test Results of a Novel Circular Array 3-D SAR System. SHILAP Revista de lepidopterología. 2 indexed citations

13.

Shi, Jun, Degang Sun, Abbas Yongaçoğlu, Meng Zhang, & Dong Wei. (2016). Computer recognition based on the compromising emanations fingerprint. 4. 1–6. 4 indexed citations

14.

Shi, Jun, Weiqing Huang, Dong Wei, & Degang Sun. (2014). A novel method for computer video leaking signal detection. 918–923. 2 indexed citations

15.

Shi, Jun, Junguo Liu, & László Pintér. (2014). Recent evolution of China's virtual water trade: analysis of selected crops and considerations for policy. Hydrology and earth system sciences. 18(4). 1349–1357. 36 indexed citations

16.

Zhao, Danpei, et al.. (2013). High-Speed Recognition Algorithm Based on BRISK and Saliency Detection for Aerial Images. Research Journal of Applied Sciences Engineering and Technology. 5(23). 5469–5473. 1 indexed citations

17.

Wang, Xinhao, Jun Shi, & Hexiang Huang. (2008). Traffic-related air quality analysis and visualisation. Civil Engineering and Environmental Systems. 25(2). 157–166. 2 indexed citations

18.

Shi, Jun. (2008). A Cylindrical Panoramic Image Mosaics Algorithm Based on Block-Matching. Jisuanji fangzhen.

19.

Shi, Jun. (2006). Optimum Path Algorithm in Traffic Network Based on Model of Hierarchical Spatial Reasoning. Jisuanji gongcheng. 3 indexed citations

20.

Shi, Zhongzhi & Jun Shi. (2004). Perspectives on cognitive informatics. 93. 129–133. 6 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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