Ke Lin

80 papers receiving 2.4k citations

Hit Papers

MFDNet: Collaborative Poses Perception and Matrix Fisher Distribution for Head Pose Estimation 2021 · 196 citations
196202120262022202450100150

Peers

Ke Lin
Comparison fields: 5 of 147
  • Inorganic Chemistry 448
  • Industrial and Manufacturing Engineering 214
  • Environmental Engineering 306
  • Computational Mechanics 380
  • Control and Systems Engineering 357
Replace Lei Chen with:
Lei Chen China
Zhenyue Zhang China
Mahmoud M. Selim Saudi Arabia
Jiajun Wang China
K. V. Rao India
Tiejun Zhang China
Baoqing Li China
Chandima Gomes Malaysia
Guoning Chen United States
Ke Lin relative to Lei Chen China Lei Chen's profile →
Citations per field
00.5×1.5×
Lei Chen · 1×
Citations per year

Countries citing papers authored by Ke Lin

Since Specialization
Citations

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

Fields of papers citing papers by Ke Lin

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 88 papers — load more, or switch the sort, to bring in the rest.

#Work
1
MFDNet: Collaborative Poses Perception and Matrix Fisher Distribution for Head Pose Estimation
Hit paper breakdown →
2021196
2
EDMF: Efficient Deep Matrix Factorization With Review Feature Learning for Industrial Recommender System
Hit paper breakdown →
2021178
3 2019174
4 2020152
5 2006140
6 2022118
7 2021107
8 200592
9 202188
10 202080
11 202279
12 202072
13 202170
14 202168
15 201865
16 202055
17 202147
18 202244
19 202041
20 201841

About Ke Lin

Ke Lin is a scholar working on Geochemistry and Petrology, Control and Systems Engineering, Inorganic Chemistry, Artificial Intelligence and Environmental Engineering, having authored 88 papers that have together received 2.4k indexed citations. Recurring topics across this work include Reinforcement Learning in Robotics (10 papers), Radioactive element chemistry and processing (9 papers), Vibration and Dynamic Analysis (7 papers), Semiconductor Lasers and Optical Devices (7 papers), Fluid Dynamics and Vibration Analysis (7 papers), Photonic and Optical Devices (6 papers), Wind and Air Flow Studies (6 papers) and Geochemistry and Elemental Analysis (5 papers). The work is most often cited by research in Inorganic Chemistry (448 citations), Industrial and Manufacturing Engineering (214 citations), Environmental Engineering (306 citations), Computational Mechanics (380 citations) and Control and Systems Engineering (357 citations). Ke Lin has collaborated with scholars based in China, United States and Singapore. Frequent co-authors include Jiasong Wang, Zhaoli Zhang, Chengliang Liu, Dixia Fan, Jiazhang Wang, Yixiang Huang, Yihui Yuan, Ning Wang, Duantengchuan Li and Liang Gong. Their work appears in journals such as Information Sciences, Knowledge-Based Systems, IEEE Transactions on Intelligent Vehicles, Physics of Fluids and Agronomy.

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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