Jun Hui Pan

1.4k citations
108 papers · 1k · h-index 20

Impact in

    • Remote-Sensing Image Classification
    • Advanced Image Fusion Techniques
    • Satellite Image Processing and Photogrammetry
    • Automated Road and Building Extraction

Papers in

Jun Hui Pan

92 papers receiving 1k citations

Peers

Jun Hui Pan
Comparison fields: 5 of 62
  • Media Technology 363
  • Ocean Engineering 428
  • Computer Vision and Pattern Recognition 258
  • Geology 69
  • Computational Mathematics 5
Replace Daniele Cerra with:
Daniele Cerra Germany
Ming Hao China
Taejung Kim South Korea
Kaimin Sun China
Dimitrios Marmanis Germany
Stefan Auer Germany
Silvano Galliani Switzerland
Farzaneh Dadrass Javan Iran
Xiong Xu China
Victor J. D. Tsai Taiwan
Jun Hui Pan relative to Daniele Cerra Germany Daniele Cerra's profile →
Citations per field
00.5×2×3.1×
Daniele Cerra · 1×
Citations per year

Countries citing papers authored by Jun Hui Pan

Since Specialization
Citations

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

Fields of papers citing papers by Jun Hui Pan

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 108 papers — load more, or switch the sort, to bring in the rest.

#Work
1 200973
2 202450
3 201042
4 202241
5 201738
6 202034
7 201730
8 201429
9 201428
10 202427
11 201326
12 201526
13 201926
14 202126
15 201625
16 201824
17 202223
18 201322
19 202422
20 201521

About Jun Hui Pan

Jun Hui Pan is a scholar working on Media Technology, Ocean Engineering, Computer Vision and Pattern Recognition, Aerospace Engineering and Atmospheric Science, having authored 108 papers that have together received 1k indexed citations. Recurring topics across this work include Satellite Image Processing and Photogrammetry (41 papers), Remote-Sensing Image Classification (22 papers), Advanced Image Fusion Techniques (17 papers), Calibration and Measurement Techniques (7 papers), Image and Signal Denoising Methods (7 papers), Image Enhancement Techniques (7 papers), Geochemistry and Geologic Mapping (5 papers) and Advanced Neural Network Applications (5 papers). The work is most often cited by research in Media Technology (363 citations), Ocean Engineering (428 citations), Computer Vision and Pattern Recognition (258 citations), Geology (69 citations) and Computational Mathematics (5 citations). Jun Hui Pan has collaborated with scholars based in China, Hong Kong and United Kingdom. Frequent co-authors include Mi WANG, Ying Zhu, Junli Li, Jonathan Li, Qinghua Zhou, Jiarui Hu, Shuying Jin, Deren Li, Xueli Chang and Rui Li. Their work appears in journals such as IEEE Transactions on Geoscience and Remote Sensing, Remote Sensing, International Journal of Applied Earth Observation and Geoinformation, IEEE Geoscience and Remote Sensing Letters and ISPRS Journal of Photogrammetry and Remote Sensing.

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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