Liling Ge

476 citations
35 papers · 370 · h-index 9

Impact in

Papers in

Liling Ge

32 papers receiving 359 citations

Peers

Liling Ge
Comparison fields: 5 of 63
  • Media Technology 55
  • Industrial and Manufacturing Engineering 54
  • Mechanical Engineering 202
  • Mechanics of Materials 101
  • Materials Chemistry 149
Replace Sangwon Hwang with:
Sangwon Hwang South Korea
Guoquan Liu China
George E. Cook United States
Yulong Cai China
He Zhao United States
Abolfazl Zolfaghari United States
Kiwamu ASHIDA Japan
Vikram Cariapa United States
Wenrong Wu China
Marco Zago Italy
Liling Ge relative to Sangwon Hwang South Korea Sangwon Hwang's profile →
Citations per field
00.5×10×13.5×
Sangwon Hwang · 1×
Citations per year

Countries citing papers authored by Liling Ge

Since Specialization
Citations

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

Fields of papers citing papers by Liling Ge

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 23 scholars most cited alongside Liling Ge, 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 Liling Ge Line = papers co-authored together Liling Ge links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 35 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201392
2 201777
3 200841
4 201430
5 201217
6 201117
7 201113
8 200810
9 20118
10 20077
11 20146
12 20086
13 20206
14 20075
15 20195
16 20134
17 20093
18 20083
19 20232
20 20102

About Liling Ge

Liling Ge is a scholar working on Computer Vision and Pattern Recognition, Computational Mechanics, Mechanical Engineering, Media Technology and Industrial and Manufacturing Engineering, having authored 35 papers that have together received 370 indexed citations. Recurring topics across this work include Advanced Image Fusion Techniques (7 papers), Medical Image Segmentation Techniques (6 papers), Advanced Numerical Analysis Techniques (6 papers), Image and Object Detection Techniques (5 papers), Metal and Thin Film Mechanics (4 papers), Manufacturing Process and Optimization (4 papers), 3D Shape Modeling and Analysis (4 papers) and Surface Treatment and Residual Stress (3 papers). The work is most often cited by research in Media Technology (55 citations), Industrial and Manufacturing Engineering (54 citations), Mechanical Engineering (202 citations), Mechanics of Materials (101 citations) and Materials Chemistry (149 citations). Liling Ge has collaborated with scholars based in China and New Zealand. Frequent co-authors include Yingjie Zhang, Zhengxin Lu, Na Tian, Caiyin You, Weidong Zeng, Min Zhang, Saifei Zhang, Qinyang Zhao, Junwei Wang and Ying Jie Zhang. Their work appears in journals such as Measurement, The International Journal of Advanced Manufacturing Technology, The Imaging Science Journal, Applied Surface Science and Digital Signal Processing.

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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