Jiangjun Peng

24 papers receiving 943 citations

Hit Papers

Guaranteed Tensor Recovery Fused Low-rankness and Smoothness 2023 · 79 citations
790+3+6Years since publication100200300

Peers

Jiangjun Peng
Comparison fields: 5 of 64
  • Computational Mathematics 133
  • Media Technology 508
  • Computer Vision and Pattern Recognition 629
  • Computational Mechanics 334
  • Computational Theory and Mathematics 101
Replace Teng-Yu Ji with:
Teng-Yu Ji China
Yongli Wang China
Xiongjun Zhang China
Huiqian Du China
Chengda Yang United States
Qibin Zhao Japan
Martin Welk Germany
Wenbo Mei China
Donghui Li China
Minru Bai China
Jiangjun Peng relative to Teng-Yu Ji China Teng-Yu Ji's profile →
Citations per field
00.5×3.6×
Teng-Yu Ji · 1×
Citations per year

Countries citing papers authored by Jiangjun Peng

Since Specialization
Citations

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

Fields of papers citing papers by Jiangjun Peng

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Jiangjun Peng, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Jiangjun Peng Line = papers co-authored together Jiangjun Peng links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 29 papers — load more, or switch the sort, to bring in the rest.

#Work
1
Hyperspectral Image Restoration Via Total Variation Regularized Low-Rank Tensor Decomposition
Hit paper breakdown →
2017343
2 2020133
3
Guaranteed Tensor Recovery Fused Low-rankness and Smoothness
Hit paper breakdown →
202379
4 201970
5 202262
6 202251
7 201839
8 201836
9 202226
10 202317
11 202415
12 202313
13 202412
14 202311
15 202310
16 20248
17 20208
18 20247
19 20245
20 20244

About Jiangjun Peng

Jiangjun Peng is a scholar working on Computer Vision and Pattern Recognition, Media Technology, Computational Mechanics, Computational Mathematics and Radiology, Nuclear Medicine and Imaging, having authored 29 papers that have together received 960 indexed citations. Recurring topics across this work include Image and Signal Denoising Methods (19 papers), Sparse and Compressive Sensing Techniques (13 papers), Advanced Image Fusion Techniques (11 papers), Remote-Sensing Image Classification (9 papers), Advanced Neuroimaging Techniques and Applications (3 papers), Tensor decomposition and applications (3 papers), Computational Drug Discovery Methods (2 papers) and Medical Imaging Techniques and Applications (2 papers). The work is most often cited by research in Computational Mathematics (133 citations), Media Technology (508 citations), Computer Vision and Pattern Recognition (629 citations), Computational Mechanics (334 citations) and Computational Theory and Mathematics (101 citations). Jiangjun Peng has collaborated with scholars based in China, Macao and Hong Kong. Frequent co-authors include Deyu Meng, Yee Leung, Yao Wang, Qian Zhao, Xi-Le Zhao, Hailin Wang, Jianjun Wang, Qi Xie, Xiangyong Cao and Hongying Zhang. Their work appears in journals such as IEEE Transactions on Geoscience and Remote Sensing, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, IEEE Transactions on Image Processing, IEEE Transactions on Pattern Analysis and Machine Intelligence and IEEE Transactions on Intelligent Transportation Systems.

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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