Yingming Li

1.0k citations
55 papers · 557 indexed · h-index 15
Co-authors
Zhongfei ZhangJiajiong CaoZenglin XuSiyu HuangTao JinBin LiuMing ChenMing Yang
Topics
Domain Adaptation and Few-Shot Learning (15 papers)Advanced Image and Video Retrieval Techniques (10 papers)Multimodal Machine Learning Applications (8 papers)

In The Last Decade

Yingming Li

50 papers receiving 541 citations

Peers

Yingming Li
Comparison fields: 5 of 87
  • Computer Vision and Pattern Recognition 339
  • Artificial Intelligence 264
  • Signal Processing 49
  • Information Systems 41
  • Experimental and Cognitive Psychology 22
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Kun Bai China
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Citations per field
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Citations per year

Countries citing papers authored by Yingming Li

Since Specialization
Citations

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

Fields of papers citing papers by Yingming Li

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Yingming Li

This figure shows the co-authorship network connecting the top 25 collaborators of Yingming Li. A scholar is included among the top collaborators of Yingming Li 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 Yingming Li. Yingming Li 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 3
2 1
3 1
4 2
5 4
6 1
7 0
8 23
9 20
10 20
11 28
12 29
13
Relative Attribute Learning with Deep Attentive Cross-image Representation
1
14
TVT: Two-View Transformer Network for Video Captioning.
16
15 32
16
Pyramid Person Matching Network for Person Re-identification
2
17
Multi-view learning with limited and noisy tagging
4
18
Multi-View Representation Learning: A Survey from Shallow Methods to Deep Methods
24
19
Hierarchical Probabilistic Matrix Factorization with Network Topology for Multi-relational Social Network
2
20
Multi-Task Learning with Gaussian Matrix Generalized Inverse Gaussian Model
16

About Yingming Li

Yingming Li is a scholar working on Computational Mathematics, Computer Vision and Pattern Recognition and Artificial Intelligence, having authored 55 papers that have together received 557 indexed citations. Recurring topics across this work include Domain Adaptation and Few-Shot Learning (15 papers), Advanced Image and Video Retrieval Techniques (10 papers) and Multimodal Machine Learning Applications (8 papers). The work is most often cited by research in Computational Mathematics (16 citations), Computer Vision and Pattern Recognition (339 citations) and Artificial Intelligence (264 citations). Yingming Li has collaborated with scholars based in China, United States and United Kingdom. Frequent co-authors include Zhongfei Zhang, Jiajiong Cao, Zenglin Xu, Siyu Huang, Tao Jin, Bin Liu, Ming Chen, Ming Yang, Ming Yang and Bin Li. Their work appears in journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, IEEE Transactions on Image Processing and Neurocomputing.

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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