Yue Cao

72 papers receiving 2.9k citations

Hit Papers

Transferable Representation Learning with Deep Adaptation...201620262019202220182016100200300400

Peers

Yue Cao
Comparison fields: 5 of 158
  • Computer Vision and Pattern Recognition 1.5k
  • Artificial Intelligence 779
  • Electrical and Electronic Engineering 275
  • Control and Systems Engineering 256
  • Mechanical Engineering 213
Replace Zhennao Cai with:
Zhennao Cai China
Qian Wang China
Cen Chen China
Wenming Cao China
Wenyuan Dai China
Zhuo Li China
Wenhai Wang China
Fuxin Li United States
Yue Cao relative to Zhennao Cai China Zhennao Cai's profile →
Citations per field
00.5×7.5×
Zhennao Cai · 1×
Citations per year

Countries citing papers authored by Yue Cao

Since Specialization
Citations

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

Fields of papers citing papers by Yue Cao

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Yue Cao

This figure shows the co-authorship network connecting the top 25 collaborators of Yue Cao. A scholar is included among the top collaborators of Yue Cao 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 Yue Cao. Yue Cao 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 4
2 2
3 15
4 21
5 9
6 0
7 68
8 16
9 2
10 10
11 11
12 4
13 16
14 2
15
Transferable Representation Learning with Deep Adaptation Networksbreakdown →
489
16 77
17 7
18 148
19
Analysis of Control Conflict between UPFC Multiple Control Functions and Their Interaction Indicator
15
20
Control interactions of UPFC multi-control control functions - analysis
4

About Yue Cao

Yue Cao is a scholar working on Computer Vision and Pattern Recognition, Control and Systems Engineering and Industrial and Manufacturing Engineering, having authored 78 papers that have together received 3.0k indexed citations. Recurring topics across this work include Advanced Image and Video Retrieval Techniques (8 papers), Welding Techniques and Residual Stresses (7 papers) and Manufacturing Process and Optimization (6 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (1.5k citations), Artificial Intelligence (779 citations) and Media Technology (101 citations). Yue Cao has collaborated with scholars based in China, United States and Japan. Frequent co-authors include Mingsheng Long, Jianmin Wang, Han Zhu, Michael I. Jordan, Zhangjie Cao, Philip S. Yu, Bo Zhao, Chuangxin Guo, Shichen Liu and Zheng Zhang. Their work appears in journals such as Proceedings of the National Academy of Sciences, IEEE Transactions on Pattern Analysis and Machine Intelligence and Journal of Cleaner Production.

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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