De-Nian Yang

2.9k citations
175 papers · 2.0k indexed · h-index 26

Impact in

Papers in

De-Nian Yang

160 papers receiving 1.9k citations

Peers

De-Nian Yang
Comparison fields: 5 of 96
  • Human-Computer Interaction 352
  • Computer Networks and Communications 784
  • Signal Processing 267
  • Statistical and Nonlinear Physics 233
  • Computer Vision and Pattern Recognition 361
Replace Ashutosh Garg with:
Ashutosh Garg United States
Shojiro Nishio Japan
James J. Thomas United States
Giuseppe Santucci Italy
Raimund Schatz Austria
Benjamin Lee United States
Kang Zhang United States
George Robertson United States
Fabian Beck Germany
Bo Han United States
De-Nian Yang relative to Ashutosh Garg United States Ashutosh Garg's profile →
Citations per field
00.5×4.3×
Ashutosh Garg · 1×
Citations per year

Countries citing papers authored by De-Nian Yang

Since Specialization
Citations

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

Fields of papers citing papers by De-Nian Yang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network

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

All Works

20 of 20 papers shown
#Work
1 20251
2 20250
3 20251
4 20240
5 20240
6 20240
7 20241
8 20241
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10 20231
11 20232
12 20231
13 20223
14 20223
15 202012
16 20204
17 202026
18 20170
19 201734
20 201430

About De-Nian Yang

De-Nian Yang is a scholar working on Computer Networks and Communications, Human-Computer Interaction, Computational Mathematics, Signal Processing and Statistical and Nonlinear Physics, having authored 175 papers that have together received 2.0k indexed citations. Recurring topics across this work include Complex Network Analysis Techniques (29 papers), Image and Video Quality Assessment (20 papers), Cooperative Communication and Network Coding (19 papers), Caching and Content Delivery (19 papers), Interactive and Immersive Displays (18 papers), Data Management and Algorithms (17 papers), Software-Defined Networks and 5G (16 papers) and Advanced MIMO Systems Optimization (16 papers). The work is most often cited by research in Human-Computer Interaction (352 citations), Computer Networks and Communications (784 citations), Signal Processing (267 citations), Statistical and Nonlinear Physics (233 citations) and Computer Vision and Pattern Recognition (361 citations). De-Nian Yang has collaborated with scholars based in Taiwan, United States and China. Frequent co-authors include Ming-Syan Chen⋆, Wang-Chien Lee, Wanjiun Liao, Wen-Tsuen Chen, Liang-Hao Huang, Bing‐Yu Chen, Rong-Hao Liang, Philip S. Yu, Shan-Hsiang Shen and Liwei Chan. Their work appears in journals such as IEEE Transactions on Knowledge and Data Engineering, IEEE Transactions on Mobile Computing, IEEE Transactions on Services Computing, IEEE Transactions on Parallel and Distributed Systems and Electronics Letters.

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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