Ting Yu

769 total citations
29 papers, 474 citations indexed

About

Ting Yu is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Aerospace Engineering. According to data from OpenAlex, Ting Yu has authored 29 papers receiving a total of 474 indexed citations (citations by other indexed papers that have themselves been cited), including 17 papers in Computer Vision and Pattern Recognition, 8 papers in Artificial Intelligence and 3 papers in Aerospace Engineering. Recurrent topics in Ting Yu's work include Multimodal Machine Learning Applications (9 papers), Human Pose and Action Recognition (5 papers) and Advanced Image and Video Retrieval Techniques (5 papers). Ting Yu is often cited by papers focused on Multimodal Machine Learning Applications (9 papers), Human Pose and Action Recognition (5 papers) and Advanced Image and Video Retrieval Techniques (5 papers). Ting Yu collaborates with scholars based in China, Australia and Singapore. Ting Yu's co-authors include Jun Yu, Dacheng Tao, Yu Zhou, Junwei Liang, Kevin Murphy, Lu Jiang, Alexander G. Hauptmann, Yueting Zhuang, Yibing Zhan and Dejing Xu and has published in prestigious journals such as SHILAP Revista de lepidopterología, IEEE Transactions on Image Processing and International Journal of Computer Vision.

In The Last Decade

Ting Yu

24 papers receiving 463 citations

Peers

Ting Yu
Comparison fields: 5 of 73
  • Computer Vision and Pattern Recognition 351
  • Artificial Intelligence 236
  • Automotive Engineering 95
  • Safety, Risk, Reliability and Quality 42
  • Signal Processing 24
Replace B. Boghossian with:
B. Boghossian United Kingdom
Xianzhi Du United States
Lingxiao Li Australia
Dangwei Li China
I‐Hong Jhuo Taiwan
Shijie Yang China
Hajer Fradi France
Yihong Xu China
Tianhong Dai United Kingdom
Rulin Huang United States
B. Boghossian United Kingdom View profile →
Citations per field, relative to Ting Yu
Ting Yu · 1×
Citations per year, relative to Ting Yu
Ting Yu · 1×

Countries citing papers authored by Ting Yu

Since Specialization
Citations

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

Fields of papers citing papers by Ting Yu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Ting Yu

This figure shows the co-authorship network connecting the top 25 collaborators of Ting Yu. A scholar is included among the top collaborators of Ting Yu 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 Ting Yu. Ting Yu 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
# Work Indexed citations
1 0
2 0
3 0
4 2
5 8
6 3
7 5
8 1
9 48
10 1
11 112
12 30
13 2
14 131
15 2
16 1
17 5
18 1
19 10
20 11

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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