Lang Nie

698 citations
29 papers · 285 · h-index 9

Impact in

    • Advanced Image and Video Retrieval Techniques
    • Advanced Vision and Imaging
    • Advanced Image Processing Techniques
    • Advanced Neural Network Applications
    • Image Retrieval and Classification Techniques
    • 3D Surveying and Cultural Heritage

Papers in

Lang Nie

23 papers receiving 283 citations

Peers

Lang Nie
Comparison fields: 5 of 34
  • Computer Vision and Pattern Recognition 251
  • Geology 20
  • Computer Graphics and Computer-Aided Design 12
  • Media Technology 30
  • Aerospace Engineering 74
Replace Chengzhou Tang with:
Chengzhou Tang Canada
Yu-Chuan Su United States
Enliang Zheng United States
Khoi Nguyen United States
Menghua Zhai United States
Karel Lebeda United Kingdom
Fu-En Wang Taiwan
Federico Camposeco Switzerland
Zhiguang Yang China
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Citations per field
00.5×6.4×
Chengzhou Tang · 1×
Citations per year

Countries citing papers authored by Lang Nie

Since Specialization
Citations

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

Fields of papers citing papers by Lang Nie

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Lang Nie, 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 Lang Nie Line = papers co-authored together Lang Nie 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 202076
2 202340
3 202236
4 202130
5 202317
6 202312
7 202311
8 202310
9 20219
10 20228
11 20237
12 20245
13 20245
14 20243
15 20233
16 20232
17 20252
18 20232
19 20242
20 20222

About Lang Nie

Lang Nie is a scholar working on Computer Vision and Pattern Recognition, Aerospace Engineering, Media Technology, Computer Graphics and Computer-Aided Design and Molecular Biology, having authored 29 papers that have together received 285 indexed citations. Recurring topics across this work include Advanced Vision and Imaging (21 papers), Advanced Image and Video Retrieval Techniques (11 papers), Robotics and Sensor-Based Localization (7 papers), Image Processing Techniques and Applications (6 papers), Advanced Image Processing Techniques (6 papers), Optical measurement and interference techniques (6 papers), Computer Graphics and Visualization Techniques (3 papers) and Radio Frequency Integrated Circuit Design (2 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (251 citations), Geology (20 citations), Computer Graphics and Computer-Aided Design (12 citations), Media Technology (30 citations) and Aerospace Engineering (74 citations). Lang Nie has collaborated with scholars based in China, Singapore and Australia. Frequent co-authors include Chunyu Lin, Yao Zhao, Kang Liao, Shuaicheng Liu, Meiqin Liu, Kang Liao, Chun-Yu Lin, Yao Zhao, Xin Li and Fan Yang. Their work appears in journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, Journal of Visual Communication and Image Representation, IEEE Transactions on Circuits and Systems for Video Technology, Forests and Computational Visual Media.

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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