Ge Yan

16 papers receiving 178 citations

Peers

Ge Yan
Comparison fields: 5 of 70
  • Automotive Engineering 19
  • Electronic, Optical and Magnetic Materials 28
  • Information Systems and Management 10
  • Electrical and Electronic Engineering 83
  • Renewable Energy, Sustainability and the Environment 22
Replace Slavka Tzanova with:
Slavka Tzanova Bulgaria
Yiliang Shi China
Weijian Zheng United States
N. Cao China
Shakir Zaman South Korea
Harshit Gupta India
Hoda Akbari Ireland
Zenan Li China
Zekun Zhang China
Hangchen Liu China
Ge Yan relative to Slavka Tzanova Bulgaria Slavka Tzanova's profile →
Citations per field
00.5×
Slavka Tzanova · 1×
Citations per year

Countries citing papers authored by Ge Yan

Since Specialization
Citations

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

Fields of papers citing papers by Ge Yan

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

18 of 18 papers shown
#Work
1 200491
2 202323
3 202320
4 202311
5 202210
6 20243
7 20243
8 20243
9 20223
10 20133
11 20232
12 20252
13 20242
14 20182
15 20231
16
Can Rural Land Stock-cooperation Increase Peasants’ Income? A Case Study of Four County-level Cities in Foshan during 1992—2009
20121
17 20240
18 20240

About Ge Yan

Ge Yan is a scholar working on Computer Vision and Pattern Recognition, Electrical and Electronic Engineering, Artificial Intelligence, Aerospace Engineering and Computer Networks and Communications, having authored 18 papers that have together received 180 indexed citations. Recurring topics across this work include Advanced Measurement and Detection Methods (2 papers), Advanced Neural Network Applications (2 papers), Artificial Intelligence in Games (1 paper), Digital Games and Media (1 paper), Robotics and Sensor-Based Localization (1 paper), Medical Image Segmentation Techniques (1 paper), Rural development and sustainability (1 paper) and Advanced Photocatalysis Techniques (1 paper). The work is most often cited by research in Automotive Engineering (19 citations), Electronic, Optical and Magnetic Materials (28 citations), Information Systems and Management (10 citations), Electrical and Electronic Engineering (83 citations) and Renewable Energy, Sustainability and the Environment (22 citations). Ge Yan has collaborated with scholars based in China, United States and Australia. Frequent co-authors include You‐Zhao Lan, Huaiyong Zhu, Xueping Gao, Feng Wu, Deying Song, Weina Qu, Huaming Wu, Chunsheng Zhu, Chaogang Tang and Wei Li. Their work appears in journals such as Transportation Research Part F Traffic Psychology and Behaviour, Remote Sensing, IEEE Transactions on Consumer Electronics, Heliyon and European Journal of Surgical Oncology.

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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