Ming Lin

1.7k citations
54 papers · 906 · h-index 15

Impact in

    • Human Pose and Action Recognition
    • Video Analysis and Summarization
    • Multimodal Machine Learning Applications
    • Video Surveillance and Tracking Methods
    • Advanced Neural Network Applications
    • Advanced Image and Video Retrieval Techniques
    • Anomaly Detection Techniques and Applications
    • Domain Adaptation and Few-Shot Learning

Papers in

Ming Lin

49 papers receiving 860 citations

Peers

Ming Lin
Comparison fields: 5 of 114
  • Computer Vision and Pattern Recognition 550
  • Artificial Intelligence 399
  • Signal Processing 92
  • Human-Computer Interaction 36
  • Computational Mathematics 3
Replace Seok-Hee Hong with:
Seok-Hee Hong Australia
Alex Hauptmann United States
Mostafa Dehghani Netherlands
Fred Hohman United States
Haidong Zhang China
Jia Chen China
Sung-Jin Kim South Korea
Yimin Chen China
Ming Lin relative to Seok-Hee Hong Australia Seok-Hee Hong's profile →
Citations per field
00.5×2.5×
Seok-Hee Hong · 1×
Citations per year

Countries citing papers authored by Ming Lin

Since Specialization
Citations

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

Fields of papers citing papers by Ming Lin

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 54 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2015176
2 2017160
3 202175
4 201567
5 201646
6 200433
7 200629
8 200624
9 202024
10 201519
11 200817
12 200517
13
Online Kernel Learning with a Near Optimal Sparsity Bound
201316
14 201216
15 201814
16 202413
17 200412
18 201510
19 20189
20 20199

About Ming Lin

Ming Lin is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence, Sociology and Political Science, Biomedical Engineering and Information Systems, having authored 54 papers that have together received 906 indexed citations. Recurring topics across this work include Video Analysis and Summarization (10 papers), Domain Adaptation and Few-Shot Learning (6 papers), Face and Expression Recognition (5 papers), Information and Cyber Security (5 papers), Human Pose and Action Recognition (5 papers), Sparse and Compressive Sensing Techniques (5 papers), Machine Learning and Algorithms (5 papers) and Multimedia Communication and Technology (4 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (550 citations), Artificial Intelligence (399 citations), Signal Processing (92 citations), Human-Computer Interaction (36 citations) and Computational Mathematics (3 citations). Ming Lin has collaborated with scholars based in United States, China and Australia. Frequent co-authors include Alexander G. Hauptmann, Yi Yang, Zhenzhong Lan, Bhiksha Raj, Xuanchong Li, Xiaojun Chang, Alexander G. Hauptmann, Zhigang Ma, Jay F. Nunamaker and Chuang Gan. Their work appears in journals such as Journal of the Association for Information Systems, IEEE Transactions on Image Processing, IEEE Transactions on Neural Networks and Learning Systems, Measurement and ITE Transactions on Media Technology 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.

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