Runyu Fan

967 citations
28 papers · 668 indexed · 1 hit paper · h-index 14

Impact in

Papers in

Runyu Fan

25 papers receiving 647 citations

Hit Papers

A survey of machine learning and deep learning in remote sensing of geological environment: Challenges, advances, and opportunities 2023 · 140 citations
14020232026202420254080120

Peers

Runyu Fan
Comparison fields: 5 of 84
  • Media Technology 258
  • Computer Vision and Pattern Recognition 158
  • Atmospheric Science 113
  • Environmental Engineering 87
  • Ocean Engineering 79
Replace Conrad M Albrecht with:
Conrad M Albrecht Germany
Jicheng Wang China
Jingliang Hu Germany
Runmin Dong China
Wenyuan Li China
Lloyd Haydn Hughes Germany
Anand Vetrivel Netherlands
Rodrigo Caye Daudt Switzerland
Xianping Ma China
Jianwen Ma China
Runyu Fan relative to Conrad M Albrecht Germany Conrad M Albrecht's profile →
Citations per field
00.5×1.5×1.8×
Conrad M Albrecht · 1×
Citations per year

Countries citing papers authored by Runyu Fan

Since Specialization
Citations

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

Fields of papers citing papers by Runyu Fan

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network

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

All Works

20 of 20 papers shown
#Work
1 20251
2 20257
3 20251
4 20250
5 20251
6 20254
7 20251
8 20247
9 20249
10 20241
11 202312
12
A survey of machine learning and deep learning in remote sensing of geological environment: Challenges, advances, and opportunities
Hit paper breakdown →
2023140
13 20220
14 202243
15 202227
16 202216
17 202211
18 202123
19 202031
20 202052

About Runyu Fan

Runyu Fan is a scholar working on Media Technology, Computer Vision and Pattern Recognition, Atmospheric Science, Geography, Planning and Development and Global and Planetary Change, having authored 28 papers that have together received 668 indexed citations. Recurring topics across this work include Remote-Sensing Image Classification (13 papers), Land Use and Ecosystem Services (7 papers), Remote Sensing and Land Use (7 papers), Automated Road and Building Extraction (4 papers), Video Surveillance and Tracking Methods (4 papers), Remote Sensing and LiDAR Applications (3 papers), Geochemistry and Geologic Mapping (3 papers) and Graphene research and applications (2 papers). The work is most often cited by research in Media Technology (258 citations), Computer Vision and Pattern Recognition (158 citations), Atmospheric Science (113 citations), Environmental Engineering (87 citations) and Ocean Engineering (79 citations). Runyu Fan has collaborated with scholars based in China and Macao. Frequent co-authors include Lizhe Wang, Wei Han, Ruyi Feng, Jining Yan, Jun Li, Xiaohan Zhang, Sheng Wang, Weijing Song, Xiaodao Chen and Yi Wang. 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, International Journal of Applied Earth Observation and Geoinformation, ISPRS Journal of Photogrammetry and Remote Sensing and Scientific Data.

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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