Can Yang

451 citations
20 papers · 300 · h-index 8

Impact in

Papers in

Can Yang

17 papers receiving 294 citations

Peers

Can Yang
Comparison fields: 5 of 54
  • Computer Vision and Pattern Recognition 196
  • Management Science and Operations Research 44
  • Computer Networks and Communications 73
  • Signal Processing 27
  • Finance 17
Replace Chika Yinka-Banjo with:
Chika Yinka-Banjo Nigeria
Ismael Jannoud Jordan
Jianhua Ma Japan
Lakmal Rupasinghe Sri Lanka
Srinath Doss Botswana
Yasushi Kambayashi Japan
Wee Hyong Tok Singapore
Nataliya Boyko Ukraine
Maman Abdurohman Indonesia
Sangita Chaudhari India
Can Yang relative to Chika Yinka-Banjo Nigeria Chika Yinka-Banjo's profile →
Citations per field
00.5×11.5×
Chika Yinka-Banjo · 1×
Citations per year

Countries citing papers authored by Can Yang

Since Specialization
Citations

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

Fields of papers citing papers by Can Yang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 21 scholars most cited alongside Can 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 Can Yang Line = papers co-authored together Can Yang links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown
#Work
1 2018123
2 202049
3 201648
4 201515
5 202012
6 201810
7 20197
8 20117
9 20177
10 20216
11 20145
12 20094
13 20093
14 20201
15 20201
16 20101
17 20061
18 20090
19
Optimization on Batching Schedule Policy for Video-On-Demand System
20020
20 20090

About Can Yang

Can Yang is a scholar working on Computer Networks and Communications, Sociology and Political Science, Computer Vision and Pattern Recognition, Information Systems and Artificial Intelligence, having authored 20 papers that have together received 300 indexed citations. Recurring topics across this work include Multimedia Communication and Technology (9 papers), Peer-to-Peer Network Technologies (7 papers), Caching and Content Delivery (7 papers), Video Analysis and Summarization (4 papers), Recommender Systems and Techniques (3 papers), Network Security and Intrusion Detection (2 papers), Internet Traffic Analysis and Secure E-voting (2 papers) and Image and Video Quality Assessment (2 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (196 citations), Management Science and Operations Research (44 citations), Computer Networks and Communications (73 citations), Signal Processing (27 citations) and Finance (17 citations). Can Yang has collaborated with scholars based in China, United States and Hong Kong. Frequent co-authors include Jianming Lv, Qing Li, Junjie Zhai, Yong Liu, Di Wu, Min Chen, Guoqing Zhang, Houwei Cao, Guoqiang Han and Yong Liu. Their work appears in journals such as IEEE Transactions on Multimedia, Applied Sciences, IEEE Access, IEEE Transactions on Information Forensics and Security and IEEE Transactions on Circuits and Systems for Video Technology.

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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