Yun Lin

2.7k citations
139 papers · 1.6k · 1 hit paper · h-index 21

Impact in

Papers in

Yun Lin

107 papers receiving 1.6k citations

Yun Lin's Hit Papers

Large-scale real-world radio signal recognition with deep learning 2021 · 196 citations
1960+1+3Years since publication50100150

Peers

Yun Lin
Comparison fields: 5 of 84
  • Artificial Intelligence 1.1k
  • Signal Processing 253
  • Aerospace Engineering 361
  • Computer Vision and Pattern Recognition 236
  • Electrical and Electronic Engineering 471
Replace Ya Tu with:
Ya Tu China
Zheng Dou China
Sangjin Hong United States
Chenxi Liu China
Shaojing Su China
Jinlong Sun China
Xiaofu Wu China
Zhutian Yang China
Yun Lin relative to Ya Tu China Ya Tu's profile →
Citations per field
00.5×1.5×2.2×
Ya Tu · 1×
Citations per year

Countries citing papers authored by Yun Lin

Since Specialization
Citations

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

Fields of papers citing papers by Yun Lin

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 139 papers — load more, or switch the sort, to bring in the rest.

#Work
1
Large-scale real-world radio signal recognition with deep learning
Hit paper breakdown →
2021196
2 2022113
3 202296
4 202192
5 202082
6 202381
7 202377
8 202037
9 202337
10 202337
11 202336
12 202335
13 202434
14 202334
15 202330
16 202029
17 202227
18 202426
19 202323
20 202322

About Yun Lin

Yun Lin is a scholar working on Artificial Intelligence, Electrical and Electronic Engineering, Aerospace Engineering, Signal Processing and Computer Vision and Pattern Recognition, having authored 139 papers that have together received 1.6k indexed citations. Recurring topics across this work include Wireless Signal Modulation Classification (73 papers), Radar Systems and Signal Processing (21 papers), Adversarial Robustness in Machine Learning (13 papers), UAV Applications and Optimization (10 papers), Internet Traffic Analysis and Secure E-voting (10 papers), Machine Learning and ELM (8 papers), Speech and Audio Processing (8 papers) and Integrated Circuits and Semiconductor Failure Analysis (7 papers). The work is most often cited by research in Artificial Intelligence (1.1k citations), Signal Processing (253 citations), Aerospace Engineering (361 citations), Computer Vision and Pattern Recognition (236 citations) and Electrical and Electronic Engineering (471 citations). Yun Lin has collaborated with scholars based in China, Japan and United States. Frequent co-authors include Guan Gui, Yu Wang, Shiwen Mao, Ya Tu, Haoran Zha, Fumiyuki Adachi, Yuchao Liu, Xue Fu, Yang Peng and Sicheng Zhang. Their work appears in journals such as IEEE Internet of Things Journal, IEEE Transactions on Cognitive Communications and Networking, IEEE Transactions on Information Forensics and Security, IEEE Transactions on Vehicular Technology and IEEE Transactions on Reliability.

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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