2020

• Grüning, Philipp and Palumbo, Alex and Zille, Marietta and Barth, Erhardt and Mamlouk, Amir Madany: A task-dependent active learning method for axon segmentation with CNNs. Proceedings on Automation in Medical Engineering, no. 1, pp. 025-025, 2020
  

  @article{GrPaZiBaMa20,
  title={A task-dependent active learning method for axon segmentation with CNNs},
  author={Gr{\"u}ning, Philipp and Palumbo, Alex and Zille, Marietta and Barth, Erhardt and Mamlouk, Amir Madany},
  journal={Proceedings on Automation in Medical Engineering},
  volume={1},
  number={1},
  pages={025--025},
  year={2020},
  url = {http://webmail.inb.uni-luebeck.de/inb-publications/pdfs/GrPaZiBaMa20.pdf},
  }
  
  

• Grüning, Philipp and Mamlouk, Amir Madany: Deep Neural-Gas Clustering for Instance Segmentation across Imaging Experiments. in 2020 International Joint Conference on Neural Networks (IJCNN), pp. 1-8, 2020
  

  @inproceedings{GrMa20,
    title={Deep {N}eural-{G}as {C}lustering for {I}nstance {S}egmentation across {I}maging {E}xperiments},
    author={Gr{\"u}ning, Philipp and Mamlouk, Amir Madany},
    booktitle={2020 International Joint Conference on Neural Networks (IJCNN)},
    pages={1--8},
    year={2020},
    organization={IEEE},
  }
  
  

• Grüning, Philipp and Martinetz, Thomas and Barth, Erhardt: Feature Products Yield Efficient Networks. arXiv preprint arXiv:2008.07930, 2020
  

  @article{GrMaBa20,
    title={Feature Products Yield Efficient Networks},
    author={Gr{\"u}ning, Philipp and Martinetz, Thomas and Barth, Erhardt},
    journal={arXiv preprint arXiv:2008.07930},
    year={2020},
    url = {http://webmail.inb.uni-luebeck.de/inb-publications/htmls/GrMaBa20.pdf},
  }
  
  

• Grüning, Philipp and Martinetz, Thomas and Barth, Erhardt: Log-Nets: Logarithmic Feature-Product Layers Yield More Compact Networks. in Artificial Neural Networks and Machine Learning - ICANN 2020, pp. 79-91, Springer International Publishing, Cham, 2020
  

  @inproceedings{GrMaBa20a,
  author={Gr{\"u}ning, Philipp and Martinetz, Thomas and Barth, Erhardt},
  editor={Farka{\v{s}}, Igor and Masulli, Paolo and Wermter, Stefan},
  title={Log-Nets: Logarithmic Feature-Product Layers Yield More Compact Networks},
  booktitle={Artificial Neural Networks and Machine Learning -- ICANN 2020},
  year={2020},
  publisher={Springer International Publishing},
  address={Cham},
  pages={79--91},
  abstract={We introduce Logarithm-Networks (Log-Nets), a novel bio-inspired type of network architecture based on logarithms of feature maps followed by convolutions. Log-Nets are capable of surpassing the performance of traditional convolutional neural networks (CNNs) while using fewer parameters. Performance is evaluated on the Cifar-10 and ImageNet benchmarks.},
  isbn={978-3-030-61616-8},
  }