Christoph Linse, M.Sc.

Photo of Christoph Linse, M.Sc.

Raum 1.018
Institut für Neuro- und Bioinformatik
Ratzeburger Allee 160 (Geb. 64)
23562 Lübeck

Email: c.linse(at)uni-luebeck.de
Phone: +49 451 3101 5514
Fax: +49 451 3101 5504

2022

Linse, Christoph; Alshazly, Hammam; Martinetz, Thomas
A walk in the black-box: 3D visualization of large neural networks in virtual reality
Neural Computing and Applications
2022
ISSN: 0941-0643, 1433-3058
DOI:10.1007/s00521-022-07608-4
Datei: s00521-022-07608-4
Bibtex: BibTeX
@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},
}

2021

Alshazly, Hammam; Linse, Christoph; Abdalla, Mohamed; Barth, Erhardt; Martinetz, Thomas
COVID-Nets: deep CNN architectures for detecting COVID-19 using chest CT scans
PeerJ Computer Science, 7 :e655
2021
DOI:10.7717/peerj-cs.655
Datei: peerj-cs.655
Bibtex: BibTeX
@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}
}
Alshazly, Hammam; Linse, Christoph; Barth, Erhardt; Martinetz, Thomas
Explainable COVID-19 Detection Using Chest CT Scans and Deep Learning
Sensors, 21 (2) :455
2021
Herausgeber: Multidisciplinary Digital Publishing Institute
Datei: AlLiBaMa21.pdf
Bibtex: BibTeX
@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}
}
Alshazly, Hammam; Linse, Christoph; Barth, Erhardt; Idris, Sahar Ahmed; Martinetz, Thomas
Towards Explainable Ear Recognition Systems Using Deep Residual Networks
IEEE Access :1-1
2021
DOI:10.1109/ACCESS.2021.3109441
Datei: ACCESS.2021.3109441
Bibtex: BibTeX
@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

Alshazly, Hammam; Linse, Christoph; Barth, Erhardt; Martinetz, Thomas
Deep Convolutional Neural Networks for Unconstrained Ear Recognition
IEEE Access, 8 :170295--170310
2020
Herausgeber: IEEE
Datei: AlLiBaMa20.pdf
Bibtex: BibTeX
@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

Alshazly, Hammam; Linse, Christoph; Barth, Erhardt; Martinetz, Thomas
Ensembles of Deep Learning Models and Transfer Learning for Ear Recognition
sensors, 19 (19) :4139
2019
Herausgeber: Multidisciplinary Digital Publishing Institute
Datei: AlLiBaMa19.pdf
Bibtex: BibTeX
@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}
}
Alshazly, Hammam; Linse, Christoph; Barth, Erhardt; Martinetz, Thomas
Handcrafted versus CNN Features for Ear Recognition
Symmetry, 11 (12) :1493
2019
Datei: AlLiBaMa19a.pdf
Bibtex: BibTeX
@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}
}