Ke Lv

991 citations
92 papers · 633 · h-index 14

Impact in

Papers in

Ke Lv

79 papers receiving 608 citations

Peers

Ke Lv
Comparison fields: 5 of 125
  • Media Technology 75
  • Computer Vision and Pattern Recognition 179
  • Nuclear Energy and Engineering 2
  • Computer Graphics and Computer-Aided Design 13
  • Artificial Intelligence 114
Replace Jianzhong Cao with:
Jianzhong Cao China
Maurício Marengoni Brazil
Hasan Şakir Bılge Türkiye
Shoubhik Debnath United States
Zhuang Liu China
Huimin Yu China
Guanying Huo China
Brett Koonce
Yutong Bai China
Ke Lv relative to Jianzhong Cao China Jianzhong Cao's profile →
Citations per field
00.5×3.8×
Jianzhong Cao · 1×
Citations per year

Countries citing papers authored by Ke Lv

Since Specialization
Citations

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

Fields of papers citing papers by Ke Lv

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 92 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201648
2 202244
3 202336
4 202133
5 201430
6 201828
7 202026
8 202325
9 202122
10 202120
11 202117
12 201516
13 202415
14 202114
15 202413
16 201913
17 202113
18 202211
19 202211
20 202311

About Ke Lv

Ke Lv is a scholar working on Computer Vision and Pattern Recognition, Electrical and Electronic Engineering, Artificial Intelligence, Control and Systems Engineering and Computational Mechanics, having authored 92 papers that have together received 633 indexed citations. Recurring topics across this work include Advanced Neural Network Applications (8 papers), Electric Motor Design and Analysis (7 papers), Advanced Image and Video Retrieval Techniques (5 papers), Advanced Numerical Analysis Techniques (5 papers), Machine Fault Diagnosis Techniques (5 papers), Computer Graphics and Visualization Techniques (5 papers), 3D Shape Modeling and Analysis (5 papers) and Domain Adaptation and Few-Shot Learning (4 papers). The work is most often cited by research in Media Technology (75 citations), Computer Vision and Pattern Recognition (179 citations), Nuclear Energy and Engineering (2 citations), Computer Graphics and Computer-Aided Design (13 citations) and Artificial Intelligence (114 citations). Ke Lv has collaborated with scholars based in China, United States and United Kingdom. Frequent co-authors include Bin Luo, Weiqiang Wang, Lianlei Shan, Si-Bao Chen, Jikai Si, Caixia Gao, Haichao Feng, Jin Tang, Hongping Yan and Lingfeng Wang. Their work appears in journals such as Electronics, IEEE Transactions on Geoscience and Remote Sensing, IET Electric Power Applications, IEEE Access and Multimedia Tools and Applications.

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.

Explore authors with similar magnitude of impact