Philipp Koch, M.Sc.

@InProceedings{Phan2023a,
   author    = {Phan, Huy and Heremans, Elisabeth and Chén, Oliver Y. 
and Koch, Philipp and Mertins, Alfred and De Vos, Maarten},
   booktitle = {ICASSP 2023 - 2023 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)},
   title     = {Improving Automatic Sleep Staging Via Temporal 
Smoothness Regularization},
   year      = {2023},
   pages     = {1-5},
   doi       = {10.1109/ICASSP49357.2023.10095805},
}

@Article{Phan2023,
   author  = {Phan, Huy and Lorenzen, Kristian P. and Heremans, Elisabeth and Chén, Oliver Y. and Tran, Minh C. and Koch, Philipp and Mertins, Alfred and Baumert, Mathias and Mikkelsen, Kaare B. and De Vos, Maarten},
   journal = {IEEE Journal of Biomedical and Health Informatics},
   title   = {L-{SeqSleepNet}: {W}hole-cycle Long Sequence Modeling for 
Automatic Sleep Staging},
   year    = {2023},
   number  = {10},
   pages   = {4748-4757},
   volume  = {27},
   doi     = {10.1109/JBHI.2023.3303197},
}

@InProceedings{Parbs2022,
   author    = {Tim J. Parbs and Philipp Koch and Alfred Mertins},
   booktitle = {Proc. European Signal Processing Conference},
   title     = {Convolutive Attention for Image Registration},
   year      = {2022},
   address   = {Belgrade, Serbia},
   month     = sep,
   pages     = {1348--1352},
   publisher = {IEEE},
   abstract  = {Elastic registration of deformed images is a vitalcomponent of many computer vision tasks, especially whenconsidering medical image data. Deep learning techniques, particularlyU-Nets, offer state-of-the-art performance, but do notyet use the rich spatial information context available in naturalimages. We propose an augmentation based on the recentlyintroduced attention mechanism to allow a U-Net to use spatialimage context. A dedicated convolutive attention scheme hasbeen developed by calculating local similarity scores of themultidimensional inputs. Additionally, a dedicated compositeerror function based on common image similarity measures isintroduced in order to further improve the registration results.To evaluate our approach, we conducted several experiments onan augmented real-world dataset containing cardiac cine MRIscans. The comparison with state-of-the-art registration schemeshighlights the potential of our approach.}, }

@Article{Phan2022,
   author   = {Phan, Huy and Mikkelsen, Kaare and Chén, Oliver Y. and 
Koch, Philipp and Mertins, Alfred and De Vos, Maarten},
   journal  = {IEEE Transactions on Biomedical Engineering},
   title    = {SleepTransformer: Automatic Sleep Staging With 
Interpretability and Uncertainty Quantification},
   year     = {2022},
   number   = {8},
   pages    = {2456-2467},
   volume   = {69},
   abstract = {Background: Black-box skepticism is one of the main hindrances impeding deep-learning-based automatic sleep scoring from being used in clinical environments. Methods: Towards interpretability, this work proposes a sequence-to-sequence sleep-staging model, namely SleepTransformer. It is based on the transformer backbone and offers interpretability of the model's decisions at both the epoch and sequence level. We further propose a simple yet efficient method to quantify uncertainty in the model's decisions. The method, which is based on entropy, can serve as a metric for deferring low-confidence epochs to a human expert for further inspection. Results: Making sense of the transformer's self-attention scores for interpretability, at the epoch level, the attention scores are encoded as a heat map to highlight sleep-relevant features captured from the input EEG signal. At the sequence level, the attention scores are visualized as the influence of different neighboring epochs in an input sequence (i.e. the context) to recognition of a target epoch, mimicking the way manual scoring is done by human experts. Conclusion: Additionally, we demonstrate that SleepTransformer performs on par with existing methods on two databases of different sizes. Significance: Equipped with interpretability and the ability of uncertainty quantification, SleepTransformer holds promise for being integrated into clinical settings.},
   doi      = {10.1109/TBME.2022.3147187},
}

@InProceedings{Phan2021,
  author    = {Huy Phan and Huy Le Nguyen and Oliver Y Chén and Lam Pham and Philipp Koch and Ian McLoughlin and Alfred Mertins},
  booktitle = {Proc. IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)},
  title     = {Multi-view Audio and Music Classification},
  year      = {2021},
  pages     = {611--615},
}

@InProceedings{Phan2021a,
  author    = {Huy Phan and Huy Le Nguyen and Oliver Y Chén and Philipp Koch and Ngoc QK Duong and Ian McLoughlin and Alfred Mertins},
  booktitle = {Proc. IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)},
  title     = {Self-attention generative adversarial network for speech enhancement},
  year      = {2021},
  pages     = {7103--7107},
}

@InProceedings{Koch2021,
  author    = {Koch, Philipp and Mohammad-Zadeh, Kamran and Maass, Marco and Dreier, Mark and Thomsen, Ole and Parbs, Tim J. and Phan, Huy and Mertins, Alfred},
  title     = {sEMG-Based Hand Movement Regression by Prediction of Joint Angles With Recurrent Neural Networks},
  booktitle = {43nd Annual International Conference of the IEEE Engineering in Medicine \& Biology Society (EMBC)},
  year      = {2021},
  pages     = {6519--6523},
doi = {10.1109/EMBC46164.2021.9630042},
}

@Article{Phan2021b,
  author  = {Huy Phan and Oliver Y Chén and Minh C Tran and Philipp Koch and Alfred Mertins and Maarten De Vos},
  journal = {IEEE Transactions on Pattern Analysis and Machine Intelligence},
  title   = {XSleepNet: Multi-view sequential model for automatic sleep staging},
  year    = {2021},
}

@InProceedings{maass2020c,
  author    = {Maass, M. and Droigk, C. and Katzberg, F. and Koch, P. and Mertins, A.},
  booktitle = {28th European Signal Processing Conference (EUSIPCO 2020)},
  title     = {A Recovery Algorithm based on the Kaczmarz Algorithm and ADMM Splitting with Application to Convex Optimization in Magnetic Particle Imaging},
  month = {September},
  year      = {2020},
  pages    = {2135--2139},
}

@article{phan2020improving,
author={H. Phan and I. V. McLoughlin and L. Pham and O. Y. Chén and P. Koch and M. De Vos and A. Mertins},

  journal={IEEE Signal Processing Letters}, 

  title={Improving GANs for Speech Enhancement}, 

  year={2020},

  volume={27},

  number={},

  pages={1700-1704},

  doi={10.1109/LSP.2020.3025020}}

@Conference{Phan2020a,
  author    = {H. Phan and L. Pham and P. Koch and N. Q. K. Duong and I. McLoughlin and A. Mertins},
  booktitle = {5th Workshop on Detection and Classification of Acoustic Scenes and Events (DCASE 2020)},
  title     = {On Multitask Loss Function for Audio Event Detection and Localization},
  year      = {2020},
  pages     = {160-164},
}

@Article{Phan2020d,
  author  = {H. Phan and K. Mikkelsen and O. Y. Chén and P. Koch and A. Mertins and P. Kidmose and M. De Vos},
  journal = {Physiological Measurement},
  title   = {Personalized Automatic Sleep Staging with Single-Night Data: a Pilot Study with KL-Divergence Regularization},
  year    = {2020},
  pages   = {Article ID 064004},
  volume  = {41},
}

@InProceedings{Koch2020a,
  author    = {Koch, Philipp and Dreier, Mark and Larsen, Anna and Parbs, Tim J. and Maass, Marco and Phan, Huy and Mertins, Alfred},
  title     = {Regression of Hand Movements from sEMG Data with Recurrent Neural Networks},
  booktitle = {42nd Annual International Conference of the IEEE Engineering in Medicine \& Biology Society (EMBC)},
  year      = {2020},
  pages     = {3783--3787},
}

@InProceedings{Koch2020b,
  author    = {Koch, Philipp and Dreier, Mark and Maass, Marco and Phan, Huy and Mertins, Alfred},
  title     = {RNN With Stacked Architecture for sEMG based Sequence-to-Sequence Hand Gesture Recognition},
  booktitle = {28th European Signal Processing Conference (EUSIPCO)},
  year      = {2020},
  pages     = {1600-1604},
}

@Article{Phan2020b,
  author  = {H. Phan and O. Y. Chén and P. Koch and Z. Lu and I. McLoughlin and A. Mertins and M. De Vos. ,},
  journal = {IEEE Transactions on Biomedical Engineering (TBME)},
  title   = {Towards More Accurate Automatic Sleep Staging via Deep Transfer Learning},
  year    = {2020},
  }

@InProceedings{phan2019d,
  author    = {H. Phan and O. Y. Chén and P. Koch and A. Mertins and De Vos, M.},
  title     = {Deep Transfer Learning for Single-Channel Automatic Sleep Staging with Channel Mismatch},
  booktitle = {Proc. 27th European Signal Processing Conference (EUSIPCO)},
  year      = {2019},
  address   = {A Coruna, Spain},
  month     = {September},
}

@InProceedings{phan2019c,
  author    = {H. Phan and O. Y. Chén and P. Koch and A. Mertins and De Vos, M.},
  title     = {Fusion of End-to-End Deep Learning Models for Sequence-to-Sequence Sleep Staging},
  booktitle = {Proc. 41st Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)},
  year      = {2019},
  pages     = {1829-1833},
  address   = {Berlin, Germany},
  month     = {July},
}

@InProceedings{phan2019e,
  author    = {H. Phan and O. Y. Chén and L. Pham and P. Koch and De Vos, M. and I. McLoughlin and A. Mertins},
  title     = {Spatio-Temporal Attention Pooling for Audio Scene Classification},
  booktitle = {Proc. 20th Annual Conference of the International Speech Communication Association (Interspeech)},
  year      = {2019},
  pages     = {3845-3849},
  address   = {Graz, Austria},
  month     = {July},
}

@InProceedings{phan2019b,
  author    = {H. Phan and O. Y. Chén and P. Koch and L. Pham and I. McLoughlin and A. Mertins and De Vos, M.},
  title     = {Beyond Equal-Length Snippets: How Long is Sufficient to Recognize an Audio Scene?},
  booktitle = {Proc. 2019 AES Conference on Audio Forensics},
  year      = {2019},
  address   = {Porto, Portugal},
  month     = {June},
}

@InProceedings{Koch2019b,
  author    = {Koch, P. and Brügge, N. and Phan, H. and Maass, M. and Mertins, A.},
  title     = {Forked Recurrent Neural Network for Hand Gesture Classification Using Inertial Measurement Data},
  booktitle = {Proc. 44 th IEEE Intl. Conf. on Acoustics, Speech and Signal Processing (ICASSP 2019)},
  year      = {2019},
  address   = {Brighton, UK},
  month     = {May},
}

@InProceedings{phan2019a,
  author    = {Phan, H. and Chen, O. Y. and Koch, P. and Pham, L. and McLoughlin, I. and Mertins, A. and De Vos, M.},
  title     = {Unifying Isolated and Overlapping Audio Event Detection with Multi-Label Multi-Task Convolutional Recurrent Neural Networks},
  booktitle = {Proc. 44 th IEEE Intl. Conf. on Acoustics, Speech and Signal Processing (ICASSP 2019)},
  year      = {2019},
  address   = {Brighton, UK},
  month     = {May},
}

@InProceedings{Maass2019,
  author    = {Maass, M. and Droigk, C. and Koch, P. and Mertins, A.},
  title     = {A Strategy for the Extension of the Kaczmarz Algorithm to Different Priors},
  Booktitle = {9th International Workshop on Magnetic Particle Imaging (IWMPI 2019)}, 
  year      = {2019},
Pages = {111-112}, 
publisher = {Infinite Science Publishing},
address = {New York, USA}, 
month = { March},
}

@inproceedings{droigk2019multiresolution,
Author = {Droigk, Christine and Maass, Marco and Koch, Philipp and Möller, Anita and Mertins, Alfred}, 
Title = {Multiresolution Magnetic Particle Imaging of Vessel Structures with Support Detection}, 
Year = {2019}, 
Pages = {113-114}, 
Booktitle = {9th International Workshop on Magnetic Particle Imaging (IWMPI 2019)}, 
publisher = {Infinite Science Publishing},
address = {New York, USA}, 
month = {March},
}

@inproceedings{koch2019a,
Author = {Koch, P.  and Maass, M. and Bruhns, M. and Droigk, C.  and Parbs, T. J. and Mertins, A.}, 
Title = {Neural Network for Reconstruction of MPI Images}, 
Year = {2019}, 
Pages = {39--40}, 
Booktitle = {9th International Workshop on Magnetic Particle Imaging (IWMPI 2019)}, 
publisher = {Infinite Science Publishing},
address = {New York, USA}, 
month = {March},
}

@INPROCEEDINGS{8856844,
  author={P. Koch and M. Dreier and M. Maass and M. Böhme and H. Phan and A. Mertins},
  booktitle={2019 41st Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)}, 
  title={A Recurrent Neural Network for Hand Gesture Recognition based on Accelerometer Data}, 
  year={2019},
  volume={},
  number={},
  pages={5088-5091},}