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Computer Science

D-Index
30
Citations
6409
World Ranking
13884
National Ranking
669

Overview

Alfred Mertins is affiliated with the University of Lübeck in Germany and has a research portfolio encompassing topics primarily within computer science and medicine. Their work focuses on signal processing, cognitive neuroscience, computer vision and pattern recognition, pulmonary and respiratory medicine, and physiology.

The scientist's research topics include speech and audio processing, music and audio processing, obstructive sleep apnea research, EEG and brain-computer interfaces, sleep and wakefulness research, phonocardiography and auscultation techniques, as well as respiratory and cough-related research.

Frequent coauthors collaborating with Alfred Mertins are:

  • Huy Phan
  • Ian McLoughlin
  • Lam Pham
  • Philipp Koch
  • Marco Maaß

The most common publication venues for Mertins's work include:

  • arXiv (Cornell University)
  • IEEE Transactions on Biomedical Engineering
  • IEEE Journal of Biomedical and Health Informatics
  • 2021 43rd Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC)
  • IEEE Transactions on Pattern Analysis and Machine Intelligence

Recent papers authored by Alfred Mertins provide insight into the focus of their research, particularly in automatic sleep staging and related biomedical engineering fields. Notable publications include:

  • SleepTransformer: Automatic Sleep Staging With Interpretability and Uncertainty Quantification, 2022, IEEE Transactions on Biomedical Engineering
  • XSleepNet: Multi-View Sequential Model for Automatic Sleep Staging, 2021, IEEE Transactions on Pattern Analysis and Machine Intelligence
  • Towards More Accurate Automatic Sleep Staging via Deep Transfer Learning, 2020, IEEE Transactions on Biomedical Engineering
  • L-SeqSleepNet: Whole-cycle Long Sequence Modeling for Automatic Sleep Staging, 2023, IEEE Journal of Biomedical and Health Informatics
  • Pediatric Automatic Sleep Staging: A Comparative Study of State-of-the-Art Deep Learning Methods, 2022, IEEE Transactions on Biomedical Engineering

These publications suggest a strong engagement with the development and application of advanced machine learning models for sleep analysis, with multiple contributions in prominent IEEE journals and conferences.

Best Publications

  • Automatic speech recognition and speech variability: A review

    M. Benzeghiba;R. De Mori;O. Deroo;Stephane Dupont

  • Signal Analysis: Wavelets, Filter Banks, Time-Frequency Transforms and Applications

    Alfred Mertins

  • Compressed sensing reconstruction for magnetic resonance parameter mapping

    Mariya Doneva;Peter Börnert;Holger Eggers;Christian Stehning

  • SleepTransformer: Automatic Sleep Staging with Interpretability and Uncertainty Quantification.

    Huy Phan;Kaare B. Mikkelsen;Oliver Y. Chén;Philipp Koch

  • XSleepNet: Multi-View Sequential Model for Automatic Sleep Staging.

    Huy Phan;Oliver Y. Chen;Minh C. Tran;Philipp Koch

  • Sketch-based image matching Using Angular partitioning

    A. Chalechale;G. Naghdy;A. Mertins

  • Towards More Accurate Automatic Sleep Staging via Deep Transfer Learning

    Huy Phan;Oliver Y. Chen;Philipp Koch;Zongqing Lu

  • Random regression forests for acoustic event detection and classification

    Huy Phan;Marco Maaß;Radoslaw Mazur;Alfred Mertins

  • Improving GANs for Speech Enhancement

    Huy Phan;Ian V. McLoughlin;Lam Pham;Oliver Y. Chen

  • Edge image description using angular radial partitioning

    A. Chalechale;Alfred Mertins;G. Naghdy

  • Robust Audio Event Recognition with 1-Max Pooling Convolutional Neural Networks.

    Huy Phan;Lars Hertel;Marco Maass;Alfred Mertins

  • Oldenburg Logatome Speech Corpus (OLLO) for Speech Recognition Experiments with Humans and Machines

    Thorsten Wesker;Bernd T. Meyer;Kirsten Wagener;Jörn Anemüller

  • Room Impulse Response Shortening/Reshaping With Infinity- and $p$ -Norm Optimization

    A. Mertins;Tiemin Mei;M. Kallinger

  • CNN-MoE Based Framework for Classification of Respiratory Anomalies and Lung Disease Detection

    Lam Pham;Huy Phan;Ramaswamy Palaniappan;Alfred Mertins

  • Compressed sensing for chemical shift‐based water–fat separation

    Mariya Doneva;Peter Börnert;Holger Eggers;Alfred Mertins

  • Local Region Descriptors for Active Contours Evolution

    C. Darolti;A. Mertins;C. Bodensteiner;U.G. Hofmann

  • Improved Audio Scene Classification Based on Label-Tree Embeddings and Convolutional Neural Networks

    Huy Phan;Lars Hertel;Marco Maass;Philipp Koch

  • Space-Time-Frequency Code implementation in MB-OFDM UWB communications: Design criteria and performance

    Le Chung Tran;A. Mertins

  • Oversampled cosine-modulated filter banks with arbitrary system delay

    J. Kliewer;A. Mertins

  • Scalable multiresolution color image segmentation

    Fardin Akhlaghian Tab;Golshah Naghdy;Alfred Mertins

  • Iterative Source-Channel Decoding With Markov Random Field Source Models

    J. Kliewer;N. Goertz;A. Mertins

  • An Approach for Solving the Permutation Problem of Convolutive Blind Source Separation Based on Statistical Signal Models

    R. Mazur;A. Mertins

  • Combined Acoustic MIMO Channel Crosstalk Cancellation and Room Impulse Response Reshaping

    J. O. Jungmann;R. Mazur;M. Kallinger;Tiemin Mei

  • Scalable multiresolution color image segmentation with smoothness constraint

    F. Akhlaghian Tab;G. Naghdy;A. Mertins

Frequent Co-Authors

Jennifer Seberry
Jennifer Seberry University of Wollongong
Peter Börnert
Peter Börnert Philips (Finland)
Jiangtao Xi
Jiangtao Xi University of Wollongong
Thomas F. Münte
Thomas F. Münte University of Lübeck
Pierre Duhamel
Pierre Duhamel CentraleSupélec
Til Aach
Til Aach RWTH Aachen University
Richard Rose
Richard Rose Google (United States)
Xiaojing Huang
Xiaojing Huang University of Technology Sydney
Christine Klein
Christine Klein University of Lübeck

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