World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
43
Citations
9293
World Ranking
7887
National Ranking
381

Overview

Bin Yang is affiliated with the University of Stuttgart in Germany. Their research spans multiple intersecting fields including Computer Science, Medicine, and Engineering, with a notable focus on subfields such as Artificial Intelligence, Radiology, Nuclear Medicine and Imaging, Computer Vision and Pattern Recognition, Cognitive Neuroscience, and Biomedical Engineering.

The scientist's work covers diverse topics with significant emphasis on:

  • Radiomics and Machine Learning in Medical Imaging
  • Domain Adaptation and Few-Shot Learning
  • Advanced MRI Techniques and Applications
  • Advanced Neural Network Applications
  • EEG and Brain-Computer Interfaces
  • Anomaly Detection Techniques and Applications
  • Muscle activation and electromyography studies

Frequent publication venues for Bin Yang include:

  • arXiv (Cornell University)
  • Proceedings on CD-ROM - International Society for Magnetic Resonance in Medicine. Scientific Meeting and Exhibition/Proceedings of the International Society for Magnetic Resonance in Medicine, Scientific Meeting and Exhibition
  • 2022 International Joint Conference on Neural Networks (IJCNN)
  • 2021 29th European Signal Processing Conference (EUSIPCO)
  • Radiology Artificial Intelligence

Some recent papers authored or co-authored by Bin Yang include:

  • "CMGAN: Conformer-Based Metric-GAN for Monaural Speech Enhancement" (2024) published in IEEE/ACM Transactions on Audio Speech and Language Processing
  • "Independent attenuation correction of whole body [18F]FDG-PET using a deep learning approach with Generative Adversarial Networks" (2020) published in EJNMMI Research
  • "Fully Automated and Standardized Segmentation of Adipose Tissue Compartments via Deep Learning in 3D Whole-Body MRI of Epidemiologic Cohort Studies" (2020) published in Radiology Artificial Intelligence
  • "Independent brain 18F-FDG PET attenuation correction using a deep learning approach with Generative Adversarial Networks." (2020) published in PubMed
  • "Uncertainty estimation and explainability in deep learning-based age estimation of the human brain: Results from the German National Cohort MRI study" (2021) published in Computerized Medical Imaging and Graphics

Bin Yang collaborates regularly with several researchers. Notable frequent co-authors include:

  • Sergios Gatidis
  • Tobias Hepp
  • Fritz Schick
  • Thomas Küstner
  • Karim Armanious

Best Publications

  • Projection approximation subspace tracking

    Bin Yang

  • MedGAN: Medical Image Translation using GANs

    Karim Armanious;Chenming Jiang;Marc Fischer;Thomas Küstner

  • MedGAN: Medical image translation using GANs

    Karim Armanious;Karim Armanious;Chenming Jiang;Marc Fischer;Thomas Küstner

  • High-Performance Automotive Radar: A review of signal processing algorithms and modulation schemes

    Gor Hakobyan;Bin Yang

  • Emotion recognition from speech signals using new harmony features

    B. Yang;M. Lugger

  • Cramer-Rao bound and optimum sensor array for source localization from time differences of arrival

    B. Yang;J. Scheuing

  • A new approach for supervised power disaggregation by using a deep recurrent LSTM network

    Lukas Mauch;Bin Yang

  • Camera-based drowsiness reference for driver state classification under real driving conditions

    Fabian Friedrichs;Bin Yang

  • An extension of the PASTd algorithm to both rank and subspace tracking

    Bin Yang

  • ${W}$ -Band Time-Domain Multiplexing FMCW MIMO Radar for Far-Field 3-D Imaging

    Daniela Bleh;Markus Rosch;Michael Kuri;Alexander Dyck

  • The Relevance of Voice Quality Features in Speaker Independent Emotion Recognition

    M. Lugger;Bin Yang

  • Rotation-based RLS algorithms: unified derivations, numerical properties, and parallel implementations

    B. Yang;J.F. Bohme

  • Retrospective correction of motion-affected MR images using deep learning frameworks.

    Thomas Küstner;Thomas Küstner;Karim Armanious;Jiahuan Yang;Bin Yang

  • Deep Learning-based Object Classification on Automotive Radar Spectra

    Kanil Patel;Kilian Rambach;Tristan Visentin;Daniel Rusev

  • Disambiguation of TDOA Estimation for Multiple Sources in Reverberant Environments

    J. Scheuing;Bin Yang

  • Automated reference-free detection of motion artifacts in magnetic resonance images.

    Thomas Küstner;Thomas Küstner;Annika Liebgott;Annika Liebgott;Lukas Mauch;Petros Martirosian

  • Asymptotic convergence analysis of the projection approximation subspace tracking algorithms

    Bin Yang

  • Unsupervised Medical Image Translation Using Cycle-MedGAN

    Karim Armanious;Chenming Jiang;Sherif Abdulatif;Thomas Kustner

  • Different Sensor Placement Strategies for TDOA Based Localization

    Bin Yang

  • Automated Detection of Solar Cell Defects with Deep Learning

    Alexander Bartler;Lukas Mauch;Bin Yang;Michael Reuter

  • Single snapshot DOA estimation

    P. Häcker;B. Yang

Frequent Co-Authors

Michael Pfeiffer
Michael Pfeiffer Bosch Center for Artificial Intelligence
Marc L. Fischer
Marc L. Fischer Lawrence Berkeley National Laboratory
Thierry Blu
Thierry Blu Chinese University of Hong Kong
Claudia Prieto
Claudia Prieto Pontificia Universidad Católica de Chile
Michael Erb
Michael Erb Max Planck Institute for Biological Cybernetics
Aleksandar Kavcic
Aleksandar Kavcic University of Hawaii at Manoa
Daniel Weiskopf
Daniel Weiskopf University of Stuttgart
Axel Tessmann
Axel Tessmann Fraunhofer Society
Syed Ali Hassan
Syed Ali Hassan National University of Sciences and Technology
Oliver Ambacher
Oliver Ambacher University of Freiburg

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