2021

• Christoph Linse and Hammam Alshazly and Thomas Martinetz: A walk in the black-box: 3D visualization of large neural networks in virtual reality. Neural Computing and Applications, aug, 2022
  

  @article{LiAlMa22,
      author = {Christoph Linse and Hammam Alshazly and Thomas Martinetz},
      title = {A walk in the black-box: {3D} visualization of large neural networks in virtual reality},
      shorttitle = {A walk in the black-box},
      issn = {0941-0643, 1433-3058},
      language = {en},
      journal = {Neural Computing and Applications},
      month = {aug},
      year = {2022},
      urldate = {2022-08-19},
      url = {https://link.springer.com/10.1007/s00521-022-07608-4},
      doi = {10.1007/s00521-022-07608-4},
  }
  
  

• Hammam Alshazly and Christoph Linse and Mohamed Abdalla and Erhardt Barth and Thomas Martinetz: COVID-Nets: deep CNN architectures for detecting COVID-19 using chest CT scans. PeerJ Computer Science, no. 7, pp. e655, 2021
  

  @article{AlLiAbBaMa21,
  author={Hammam Alshazly and Christoph Linse and Mohamed Abdalla and Erhardt Barth and Thomas Martinetz},
  title = {{COVID-Nets}: deep {CNN} architectures for detecting {COVID-19} using chest {CT} scans},
  journal = {PeerJ Computer Science},
  volume={7},
  pages={e655},
  year={2021},
  doi = {10.7717/peerj-cs.655},
  url = {https://doi.org/10.7717/peerj-cs.655}
  }
  
  

• Hammam Alshazly and Christoph Linse and Erhardt Barth and Thomas Martinetz: Explainable COVID-19 Detection Using Chest CT Scans and Deep Learning. Sensors, no. 21, pp. 455, Multidisciplinary Digital Publishing Institute, 2021
  

  @article{AlLiBaMa21,
  author={Hammam Alshazly and Christoph Linse and Erhardt Barth and Thomas Martinetz},
  title = {Explainable {COVID-19} {D}etection {U}sing {C}hest {CT} {S}cans and {D}eep {L}earning},
  journal = {Sensors},
  volume={21},
  number={2},
  pages={455},
  year={2021},
  publisher={Multidisciplinary Digital Publishing Institute},
  url = {https://www.mdpi.com/1424-8220/21/2/455},
  url = {https://www.inb.uni-luebeck.de/fileadmin/files/publications/inb-publications/pdfs/AlLiBaMa21.pdf}
  }
  
  

• Hammam Alshazly and Christoph Linse and Erhardt Barth and Sahar Ahmed Idris and Thomas Martinetz: Towards Explainable Ear Recognition Systems Using Deep Residual Networks. IEEE Access, pp. 1-1, 2021
  

  @article{AlLiBaIdMa21,
  author = {Hammam Alshazly and Christoph Linse and Erhardt Barth and Sahar Ahmed Idris and Thomas Martinetz},
  journal = {IEEE Access},
  title = {{T}owards {E}xplainable {E}ar {R}ecognition {S}ystems {U}sing {D}eep {R}esidual {N}etworks},
  year = {2021},
  pages = {1-1},
  doi = {10.1109/ACCESS.2021.3109441},
  url = {https://doi.org/10.1109/ACCESS.2021.3109441}
  }
  
  

2020

• Hammam Alshazly and Christoph Linse and Erhardt Barth and Thomas Martinetz: Deep Convolutional Neural Networks for Unconstrained Ear Recognition. IEEE Access, no. 8, pp. 170295-170310, IEEE, 2020
  

  @article{AlLiBaMa20,
    title={Deep {C}onvolutional {N}eural {N}etworks for {U}nconstrained {E}ar {R}ecognition},
    author={Hammam Alshazly and Christoph Linse and Erhardt Barth and Thomas Martinetz},
    journal={IEEE Access},
    publisher={IEEE},
    volume={8},
    pages={170295--170310},
    year={2020},
    url = {https://www.inb.uni-luebeck.de/fileadmin/files/publications/inb-publications/pdfs/AlLiBaMa20.pdf}
  }
  
  

2019

• Hammam Alshazly and Christoph Linse and Erhardt Barth and Thomas Martinetz: Ensembles of Deep Learning Models and Transfer Learning for Ear Recognition. sensors, no. 19, pp. 4139, Multidisciplinary Digital Publishing Institute, 2019
  

  @article{AlLiBaMa19,
  author={Hammam Alshazly and Christoph Linse and Erhardt Barth and Thomas Martinetz},
  title = {Ensembles of {D}eep {L}earning {M}odels and {T}ransfer {L}earning for {E}ar {R}ecognition},
  journal = {sensors},
  volume={19},
  number={19},
  pages={4139},
  year={2019},
  publisher={Multidisciplinary Digital Publishing Institute},
  url = {https://www.mdpi.com/1424-8220/19/19/4139},
  url = {https://www.inb.uni-luebeck.de/fileadmin/files/publications/inb-publications/pdfs/AlLiBaMa19.pdf}
  }
  
  

• Hammam Alshazly and Christoph Linse and Erhardt Barth and Thomas Martinetz: Handcrafted versus CNN Features for Ear Recognition. Symmetry, no. 11, pp. 1493, 2019
  

  @article{AlLiBaMa19a,
    title={{Handcrafted versus CNN Features for Ear Recognition}},
    author={Hammam Alshazly and Christoph Linse and Erhardt Barth and Thomas Martinetz},
    journal={Symmetry},
    volume={11},
    number={12},
    pages={1493},
    year={2019},
    url = {https://www.inb.uni-luebeck.de/fileadmin/files/publications/inb-publications/pdfs/AlLiBaMa19a.pdf}
  }