Ming Zeng

2.6k citations
57 papers · 1.6k indexed · 1 hit paper · h-index 14
Topics
Face recognition and analysis (11 papers)Human Pose and Action Recognition (11 papers)Anomaly Detection Techniques and Applications (9 papers)
Partner nations
ChinaUnited StatesNorway

In The Last Decade

Ming Zeng

50 papers receiving 1.5k citations

Hit Papers

Convolutional Neural Networks for Human Activity Recognit...20142026201820222014200400600

Peers

Ming Zeng
Comparison fields: 5 of 110
  • Computer Vision and Pattern Recognition 1.2k
  • Artificial Intelligence 430
  • Biomedical Engineering 241
  • Signal Processing 198
  • Computer Networks and Communications 184
Replace Hongkai Wen with:
Hongkai Wen United Kingdom
Fabio Lavagetto Italy
Hakan Bilen United Kingdom
Ran Xu China
Noor Almaadeed Qatar
Miguel Ángel Bautista Spain
Kimiaki Shirahama Germany
Bo Dai United States
Mohsen Soryani Iran
Stephan Sigg Finland
Ming Zeng relative to Hongkai Wen United Kingdom Hongkai Wen's profile →
Citations per field
00.5×1.7×
Hongkai Wen · 1×
Citations per year

Countries citing papers authored by Ming Zeng

Since Specialization
Citations

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

Fields of papers citing papers by Ming Zeng

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Ming Zeng

This figure shows the co-authorship network connecting the top 25 collaborators of Ming Zeng. A scholar is included among the top collaborators of Ming Zeng based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Ming Zeng. Ming Zeng is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
#WorkIndexed citations
1 2
2 3
3 2
4 0
5 1
6 6
7 7
8 3
9 1
10 1
11 90
12 2
13 5
14 16
15 6
16 0
17
Convolutional Neural Networks for Human Activity Recognition using Mobile Sensorsbreakdown →
607
18 46
19 83
20
Color Segmentation of Nuclei of Blood Cell Using Support Vector Machines
2

About Ming Zeng

Ming Zeng is a scholar working on Computer Vision and Pattern Recognition, Computer Graphics and Computer-Aided Design and Artificial Intelligence, having authored 57 papers that have together received 1.6k indexed citations. Recurring topics across this work include Face recognition and analysis (11 papers), Human Pose and Action Recognition (11 papers) and Anomaly Detection Techniques and Applications (9 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (1.2k citations), Signal Processing (198 citations) and Artificial Intelligence (430 citations). Ming Zeng has collaborated with scholars based in China, United States and Norway. Frequent co-authors include Le T. Nguyen, Joy Zhang, Ole J. Mengshoel, Pang Wu, Bo Yu, Jiang Zhu, Fang Wen, Yinglin Zheng, Dong Chen and Jianmin Bao. Their work appears in journals such as Polymer, Sensors and Information Sciences.

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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