Bin Yang

194 papers receiving 3.4k citations

Bin Yang's Hit Papers

CMGAN: Conformer-Based Metric-GAN for Monaural Speech Enhancement 2024 · 48 citations
480+1Years since publication10203040

Peers

Bin Yang
Comparison fields: 5 of 135
  • Signal Processing 575
  • Aerospace Engineering 790
  • Radiology, Nuclear Medicine and Imaging 516
  • Computer Vision and Pattern Recognition 537
  • Artificial Intelligence 692
Replace John J. Soraghan with:
John J. Soraghan United Kingdom
Chengdong Wu China
Mu Zhou China
Jiquan Ngiam United States
Feng Jiang China
Xinge You China
Shaoyi Du China
Dong Seog Han South Korea
Munawar Hayat Australia
Bin Yang relative to John J. Soraghan United Kingdom John J. Soraghan's profile →
Citations per field
00.5×4.8×
John J. Soraghan · 1×
Citations per year

Countries citing papers authored by Bin Yang

Since Specialization
Citations

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

Fields of papers citing papers by Bin Yang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 208 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2019212
2 2015163
3 2017134
4 2006120
5 2007111
6 201099
7 201997
8 201989
9 201080
10 201778
11 201777
12 201976
13 201876
14 199573
15 201759
16 200755
17 202054
18 200654
19 201648
20
CMGAN: Conformer-Based Metric-GAN for Monaural Speech Enhancement
Hit paper breakdown →
202448

About Bin Yang

Bin Yang is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence, Aerospace Engineering, Signal Processing and Radiology, Nuclear Medicine and Imaging, having authored 208 papers that have together received 3.5k indexed citations. Recurring topics across this work include Radar Systems and Signal Processing (30 papers), Advanced SAR Imaging Techniques (27 papers), Advanced Neural Network Applications (17 papers), Domain Adaptation and Few-Shot Learning (16 papers), Direction-of-Arrival Estimation Techniques (15 papers), Speech and Audio Processing (15 papers), Blind Source Separation Techniques (13 papers) and Medical Imaging Techniques and Applications (13 papers). The work is most often cited by research in Signal Processing (575 citations), Aerospace Engineering (790 citations), Radiology, Nuclear Medicine and Imaging (516 citations), Computer Vision and Pattern Recognition (537 citations) and Artificial Intelligence (692 citations). Bin Yang has collaborated with scholars based in Germany, China and United States. Frequent co-authors include Gor Hakobyan, Lukas Mauch, Sergios Gatidis, Thomas Küstner, Marko Lugger, Karim Armanious, Fritz Schick, Sherif Abdulatif, Konstantin Nikolaou and Yi-Wen Liao. Their work appears in journals such as IEEE Transactions on Signal Processing, IEEE Transactions on Aerospace and Electronic Systems, Magnetic Resonance in Medicine, Journal of Magnetic Resonance Imaging and Radiology Artificial Intelligence.

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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