Ming Yang

12.3k citations
112 papers · 7.5k indexed · 2 hit papers · h-index 36

Ming Yang

101 papers receiving 7.2k citations

Hit Papers

Track to Detect and Segment: An Onl...245201420262018202210002.0k3.0k

Peers

Ming Yang
Comparison fields: 5 of 181
  • Computer Vision and Pattern Recognition 5.9k
  • Signal Processing 1.3k
  • Media Technology 448
  • Artificial Intelligence 1.6k
  • Human-Computer Interaction 156
Replace Cees G. M. Snoek with:
Cees G. M. Snoek Netherlands
Rainer Lienhart Germany
Xian‐Sheng Hua China
Tamara L. Berg United States
Tiejun Huang China
Ran He China
Baocai Yin China
Wei Jiang China
Chenggang Yan China
Zhen Lei China
Ming Yang relative to Cees G. M. Snoek Netherlands Cees G. M. Snoek's profile →
Citations per field
00.5×1.5×2.1×
Cees G. M. Snoek · 1×
Citations per year

Countries citing papers authored by Ming Yang

Since Specialization
Citations

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

Fields of papers citing papers by Ming Yang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network

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

All Works

20 of 20 papers shown
#Work
1 20250
2 20251
3 20251
4 20250
5 20250
6 20240
7 20240
8 20241
9 20241
10 20231
11 20233
12 20211
13 2019138
14 20184
15 201812
16 201165
17 201143
18
A Novel Method of Multi-image Matching Using Image and Space Synthesis Information
20090
19 2009157
20 200728

About Ming Yang

Ming Yang is a scholar working on Computer Vision and Pattern Recognition, Media Technology, Finance, Artificial Intelligence and Signal Processing, having authored 112 papers that have together received 7.5k indexed citations. Recurring topics across this work include Video Surveillance and Tracking Methods (32 papers), Advanced Image and Video Retrieval Techniques (27 papers), Human Pose and Action Recognition (19 papers), Advanced Neural Network Applications (13 papers), Image Retrieval and Classification Techniques (12 papers), Advanced Vision and Imaging (12 papers), Face recognition and analysis (11 papers) and Multimodal Machine Learning Applications (9 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (5.9k citations), Signal Processing (1.3k citations), Media Technology (448 citations), Artificial Intelligence (1.6k citations) and Human-Computer Interaction (156 citations). Ming Yang has collaborated with scholars based in United States, China and Pakistan. Frequent co-authors include Lior Wolf, Marc’Aurelio Ranzato, Yaniv Taigman, Ying Wu, Junsong Yuan, Kai Yu, Shiliang Zhang, Yanhu Shan, Xiaoyu Wang and Gang Hua. Their work appears in journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, IEEE Transactions on Image Processing, Electronics, IEEE Transactions on Multimedia 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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