Jun Lang

1.1k citations
56 papers · 872 · h-index 17

Impact in

Papers in

Jun Lang

49 papers receiving 835 citations

Peers

Jun Lang
Comparison fields: 5 of 100
  • Computer Vision and Pattern Recognition 574
  • Applied Mathematics 179
  • Acoustics and Ultrasonics 8
  • Mathematical Physics 76
  • Media Technology 71
Replace Zhihong Zhou with:
Zhihong Zhou China
Wenying Wen China
Hala S. El‐sayed Egypt
Hengzheng Wei China
Ravi Kumar India
Shan Cheng China
Chong Fu China
Xiuli Chai China
Yi‐Hua Zhou China
Rajib Kumar Jha India
Jun Lang relative to Zhihong Zhou China Zhihong Zhou's profile →
Citations per field
00.5×3.7×
Zhihong Zhou · 1×
Citations per year

Countries citing papers authored by Jun Lang

Since Specialization
Citations

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

Fields of papers citing papers by Jun Lang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Jun Lang, 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 Jun Lang Line = papers co-authored together Jun Lang links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 56 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2008103
2 201387
3 201079
4 201478
5 201257
6 201255
7 200838
8 199835
9 200929
10 201228
11 201327
12 201024
13 202024
14 201324
15 201223
16 201822
17 200016
18 201413
19 202312
20 202210

About Jun Lang

Jun Lang is a scholar working on Computer Vision and Pattern Recognition, Applied Mathematics, Artificial Intelligence, Computational Mechanics and Signal Processing, having authored 56 papers that have together received 872 indexed citations. Recurring topics across this work include Chaos-based Image/Signal Encryption (17 papers), Mathematical Analysis and Transform Methods (15 papers), Advanced Steganography and Watermarking Techniques (11 papers), Sparse and Compressive Sensing Techniques (8 papers), Image and Signal Denoising Methods (8 papers), Digital Filter Design and Implementation (4 papers), Mathematical Dynamics and Fractals (4 papers) and Natural Language Processing Techniques (3 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (574 citations), Applied Mathematics (179 citations), Acoustics and Ultrasonics (8 citations), Mathematical Physics (76 citations) and Media Technology (71 citations). Jun Lang has collaborated with scholars based in China, United States and Singapore. Frequent co-authors include Ran Tao, Yue Wang, Yue Wang, David B. Stewart, Yue Wang, Yue Wang, Timothy J. Bradley, Clodagh O’Gorman, Catriona Syme and Greg D. Wells. Their work appears in journals such as Optics Communications, Optics and Lasers in Engineering, Digital Signal Processing, Multimedia Tools and Applications and Advanced Materials.

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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