Ke Ma

680 citations
46 papers · 437 · h-index 12

Impact in

Papers in

Ke Ma

41 papers receiving 427 citations

Peers

Ke Ma
Comparison fields: 5 of 75
  • Metals and Alloys 15
  • Mechanical Engineering 183
  • Computer Vision and Pattern Recognition 73
  • Aerospace Engineering 77
  • Bioengineering 13
Replace Hyun Park with:
Hyun Park South Korea
Jianglong Zhang China
Jihun Choi South Korea
Changqing Huang China
Zhuoyuan Li China
Chang-Hee Choi South Korea
Guoquan Liu China
He Zhao United States
Sung-Won Moon South Korea
Felix Abt Germany
Ke Ma relative to Hyun Park South Korea Hyun Park's profile →
Citations per field
00.5×1.5×2.2×
Hyun Park · 1×
Citations per year

Countries citing papers authored by Ke Ma

Since Specialization
Citations

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

Fields of papers citing papers by Ke Ma

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 46 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201282
2 201458
3 201253
4 201430
5 201321
6 200818
7 202117
8 201614
9 201814
10 201913
11 202211
12 202211
13 201910
14 20097
15 19907
16 20197
17 20146
18 20246
19 20234
20 20244

About Ke Ma

Ke Ma is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition, Mechanical Engineering, Materials Chemistry and Information Systems, having authored 46 papers that have together received 437 indexed citations. Recurring topics across this work include Adversarial Robustness in Machine Learning (5 papers), Recommender Systems and Techniques (5 papers), Welding Techniques and Residual Stresses (4 papers), ZnO doping and properties (4 papers), Risk and Safety Analysis (3 papers), Face and Expression Recognition (3 papers), Fault Detection and Control Systems (3 papers) and Imbalanced Data Classification Techniques (3 papers). The work is most often cited by research in Metals and Alloys (15 citations), Mechanical Engineering (183 citations), Computer Vision and Pattern Recognition (73 citations), Aerospace Engineering (77 citations) and Bioengineering (13 citations). Ke Ma has collaborated with scholars based in China, Hong Kong and United States. Frequent co-authors include Jihua Huang, Xingke Zhao, Shuhai Chen, Yongning He, Hua Zhang, Wenbo Peng, Xiaochun Cao, Anupam Vivek, Qingming Huang and Hua Zhong. Their work appears in journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, Sensors and Actuators A Physical, Metallurgical and Materials Transactions B, Cancer Letters and Metallurgical and Materials Transactions A.

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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