---
_id: '4205'
author:
- first_name: Sanaullah
  full_name: Sanaullah, Sanaullah
  id: '248865'
  last_name: Sanaullah
  orcid: 0000-0003-4112-802X
  orcid_put_code_url: https://api.orcid.org/v2.0/0000-0003-4112-802X/work/157718005
- first_name: 'Shamini '
  full_name: 'Koravuna, Shamini '
  last_name: Koravuna
- first_name: 'Ulrich '
  full_name: 'Rückert, Ulrich '
  last_name: Rückert
- first_name: Thorsten
  full_name: Jungeblut, Thorsten
  id: '242294'
  last_name: Jungeblut
  orcid: 0000-0001-7425-8766
citation:
  alphadin: '<span style="font-variant:small-caps;">Sanaullah, Sanaullah</span> ;
    <span style="font-variant:small-caps;">Koravuna, Shamini </span> ; <span style="font-variant:small-caps;">Rückert,
    Ulrich </span> ; <span style="font-variant:small-caps;">Jungeblut, Thorsten</span>:
    A Novel Spike Vision Approach for Robust Multi-Object Detection using SNNs. In:
    , 2023'
  ama: 'Sanaullah S, Koravuna S, Rückert U, Jungeblut T. A Novel Spike Vision Approach
    for Robust Multi-Object Detection using SNNs. In: ; 2023. doi:<a href="https://doi.org/10.5281/zenodo.10262228">10.5281/zenodo.10262228</a>'
  apa: 'Sanaullah, S., Koravuna, S., Rückert, U., &#38; Jungeblut, T. (2023). A Novel
    Spike Vision Approach for Robust Multi-Object Detection using SNNs. Presented
    at the Conference: Novel Trends in Data Science 2023, Congressi Stefano Franscini
    at Monte Verità in Ticino, Switzerland. <a href="https://doi.org/10.5281/zenodo.10262228">https://doi.org/10.5281/zenodo.10262228</a>'
  bibtex: '@inproceedings{Sanaullah_Koravuna_Rückert_Jungeblut_2023, title={A Novel
    Spike Vision Approach for Robust Multi-Object Detection using SNNs}, DOI={<a href="https://doi.org/10.5281/zenodo.10262228">10.5281/zenodo.10262228</a>},
    author={Sanaullah, Sanaullah and Koravuna, Shamini  and Rückert, Ulrich  and Jungeblut,
    Thorsten}, year={2023} }'
  chicago: Sanaullah, Sanaullah, Shamini  Koravuna, Ulrich  Rückert, and Thorsten
    Jungeblut. “A Novel Spike Vision Approach for Robust Multi-Object Detection Using
    SNNs,” 2023. <a href="https://doi.org/10.5281/zenodo.10262228">https://doi.org/10.5281/zenodo.10262228</a>.
  ieee: 'S. Sanaullah, S. Koravuna, U. Rückert, and T. Jungeblut, “A Novel Spike Vision
    Approach for Robust Multi-Object Detection using SNNs,” presented at the Conference:
    Novel Trends in Data Science 2023, Congressi Stefano Franscini at Monte Verità
    in Ticino, Switzerland, 2023.'
  mla: Sanaullah, Sanaullah, et al. <i>A Novel Spike Vision Approach for Robust Multi-Object
    Detection Using SNNs</i>. 2023, doi:<a href="https://doi.org/10.5281/zenodo.10262228">10.5281/zenodo.10262228</a>.
  short: 'S. Sanaullah, S. Koravuna, U. Rückert, T. Jungeblut, in: 2023.'
conference:
  end_date: 2023-10-25
  location: Congressi Stefano Franscini at Monte Verità in Ticino, Switzerland
  name: 'Conference: Novel Trends in Data Science 2023'
  start_date: 2023-10-22
date_created: 2024-01-04T13:00:57Z
date_updated: 2026-03-17T15:28:57Z
doi: 10.5281/zenodo.10262228
external_id:
  zenodo:
  - 10.5281/zenodo.10262227
keyword:
- Spiking Neural Network
- Neural Network
- Object Detection
language:
- iso: eng
main_file_link:
- open_access: '1'
  url: https://www.researchgate.net/publication/376229340_A_Novel_Spike_Vision_Approach_for_Robust_Multi-Object_Detection_Using_SNNs
oa: '1'
project:
- _id: beb248c8-cd75-11ed-b77c-e432b4711f7b
  name: Institut für Systemdynamik und Mechatronik
publication_status: published
status: public
title: A Novel Spike Vision Approach for Robust Multi-Object Detection using SNNs
type: conference
user_id: '242294'
year: '2023'
...
---
_id: '2953'
author:
- first_name: Grit
  full_name: Behrens, Grit
  id: '207629'
  last_name: Behrens
  orcid: 0009-0009-0247-8204
- first_name: Dennis
  full_name: Hepp, Dennis
  last_name: Hepp
- first_name: Sebastian
  full_name: Hempelmann, Sebastian
  last_name: Hempelmann
- first_name: 'Werner '
  full_name: 'Friedrich, Werner '
  last_name: Friedrich
citation:
  alphadin: '<span style="font-variant:small-caps;">Behrens, Grit</span> ; <span style="font-variant:small-caps;">Hepp,
    Dennis</span> ; <span style="font-variant:small-caps;">Hempelmann, Sebastian</span>
    ; <span style="font-variant:small-caps;">Friedrich, Werner </span>: Detection
    of snow-coverage on PV-modules with images based on CNN-techniques. In: <span
    style="font-variant:small-caps;">Wohlgemuth, V.</span> ; <span style="font-variant:small-caps;">Naumann,
    S.</span> ; <span style="font-variant:small-caps;">Arnd, H.-K.</span> ; <span
    style="font-variant:small-caps;">Behrens, G.</span> ; <span style="font-variant:small-caps;">Höb,
    M.</span> ; <span style="font-variant:small-caps;">Gesellschaft für Informatik
    e.V.</span> (Hrsg.): <i>ENVIROINFO 2022</i>, <i>Lecture Notes in Informatics (LNI)
    - Proceedings, Volume P-328</i>. Bd. P328. Bonn, 2022'
  ama: 'Behrens G, Hepp D, Hempelmann S, Friedrich W. Detection of snow-coverage on
    PV-modules with images based on CNN-techniques. In: Wohlgemuth V, Naumann S, Arnd
    H-K, Behrens G, Höb M, Gesellschaft für Informatik e.V., eds. <i>ENVIROINFO 2022</i>.
    Vol P328. Lecture Notes in Informatics (LNI) - Proceedings, Volume P-328. Bonn;
    2022.'
  apa: Behrens, G., Hepp, D., Hempelmann, S., &#38; Friedrich, W. (2022). Detection
    of snow-coverage on PV-modules with images based on CNN-techniques. In V. Wohlgemuth,
    S. Naumann, H.-K. Arnd, G. Behrens, M. Höb, &#38; Gesellschaft für Informatik
    e.V. (Eds.), <i>ENVIROINFO 2022</i> (Vol. P328). Bonn.
  bibtex: '@inproceedings{Behrens_Hepp_Hempelmann_Friedrich_2022, place={Bonn}, series={Lecture
    Notes in Informatics (LNI) - Proceedings, Volume P-328}, title={Detection of snow-coverage
    on PV-modules with images based on CNN-techniques}, volume={P328}, booktitle={ENVIROINFO
    2022}, author={Behrens, Grit and Hepp, Dennis and Hempelmann, Sebastian and Friedrich,
    Werner }, editor={Wohlgemuth, Volker  and Naumann, Stefan  and Arnd, Hans-Knud
    and Behrens, Grit  and Höb, Maximilian and Gesellschaft für Informatik e.V.Editors},
    year={2022}, collection={Lecture Notes in Informatics (LNI) - Proceedings, Volume
    P-328} }'
  chicago: Behrens, Grit, Dennis Hepp, Sebastian Hempelmann, and Werner  Friedrich.
    “Detection of Snow-Coverage on PV-Modules with Images Based on CNN-Techniques.”
    In <i>ENVIROINFO 2022</i>, edited by Volker  Wohlgemuth, Stefan  Naumann, Hans-Knud
    Arnd, Grit  Behrens, Maximilian Höb, and Gesellschaft für Informatik e.V., Vol.
    P328. Lecture Notes in Informatics (LNI) - Proceedings, Volume P-328. Bonn, 2022.
  ieee: G. Behrens, D. Hepp, S. Hempelmann, and W. Friedrich, “Detection of snow-coverage
    on PV-modules with images based on CNN-techniques,” in <i>ENVIROINFO 2022</i>,
    Hamburg, 2022, vol. P328.
  mla: Behrens, Grit, et al. “Detection of Snow-Coverage on PV-Modules with Images
    Based on CNN-Techniques.” <i>ENVIROINFO 2022</i>, edited by Volker  Wohlgemuth
    et al., vol. P328, 2022.
  short: 'G. Behrens, D. Hepp, S. Hempelmann, W. Friedrich, in: V. Wohlgemuth, S.
    Naumann, H.-K. Arnd, G. Behrens, M. Höb, Gesellschaft für Informatik e.V. (Eds.),
    ENVIROINFO 2022, Bonn, 2022.'
conference:
  end_date: 2022-09-30
  location: Hamburg
  name: EnviroInfo 2022
  start_date: 2022-09-26
corporate_editor:
- Gesellschaft für Informatik e.V.
date_created: 2023-05-23T16:08:36Z
date_updated: 2026-03-17T15:28:39Z
department:
- _id: '102'
editor:
- first_name: 'Volker '
  full_name: 'Wohlgemuth, Volker '
  last_name: Wohlgemuth
- first_name: 'Stefan '
  full_name: 'Naumann, Stefan '
  last_name: Naumann
- first_name: Hans-Knud
  full_name: Arnd, Hans-Knud
  last_name: Arnd
- first_name: 'Grit '
  full_name: 'Behrens, Grit '
  last_name: Behrens
- first_name: Maximilian
  full_name: Höb, Maximilian
  last_name: Höb
external_id:
  unknown:
  - http://dl.gi.de/handle/20.500.12116/39404
jel:
- D83
keyword:
- convolutional neural network
- photovoltaic modules
- snow detection
- machine learning
language:
- iso: eng
main_file_link:
- open_access: '1'
  url: http://dl.gi.de/handle/20.500.12116/39404
oa: '1'
place: Bonn
project:
- _id: A82B586E-C7DA-11E9-B0AE-1F4CB252D58D
  name: Adaptive Ertragsprognose mit data-Mining im PV-Feld auf Grundlage iener digitalen
    Signatur der PV-Module und der Systemkomponenten (PV digital 4.0)
publication: ENVIROINFO 2022
publication_identifier:
  isbn:
  - "\t978-3-88579-722-7"
  issn:
  - "\t1617-5468"
publication_status: published
quality_controlled: '1'
series_title: Lecture Notes in Informatics (LNI) - Proceedings, Volume P-328
status: public
title: Detection of snow-coverage on PV-modules with images based on CNN-techniques
type: conference
user_id: '237837'
volume: P328
year: '2022'
...
---
_id: '662'
article_number: '2550'
article_type: review
author:
- first_name: Tomasz
  full_name: Blachowicz, Tomasz
  last_name: Blachowicz
- first_name: Andrea
  full_name: Ehrmann, Andrea
  id: '223776'
  last_name: Ehrmann
  orcid: 0000-0003-0695-3905
  orcid_put_code_url: https://api.orcid.org/v2.0/0000-0003-0695-3905/work/160526088
citation:
  alphadin: '<span style="font-variant:small-caps;">Blachowicz, Tomasz</span> ; <span
    style="font-variant:small-caps;">Ehrmann, Andrea</span>: Magnetic Elements for
    Neuromorphic Computing. In: <i>Molecules</i> Bd. 25 (2020), Nr. 11'
  ama: Blachowicz T, Ehrmann A. Magnetic Elements for Neuromorphic Computing. <i>Molecules</i>.
    2020;25(11). doi:<a href="https://doi.org/10.3390/molecules25112550">10.3390/molecules25112550</a>
  apa: Blachowicz, T., &#38; Ehrmann, A. (2020). Magnetic Elements for Neuromorphic
    Computing. <i>Molecules</i>, <i>25</i>(11). <a href="https://doi.org/10.3390/molecules25112550">https://doi.org/10.3390/molecules25112550</a>
  bibtex: '@article{Blachowicz_Ehrmann_2020, title={Magnetic Elements for Neuromorphic
    Computing}, volume={25}, DOI={<a href="https://doi.org/10.3390/molecules25112550">10.3390/molecules25112550</a>},
    number={112550}, journal={Molecules}, author={Blachowicz, Tomasz and Ehrmann,
    Andrea}, year={2020} }'
  chicago: Blachowicz, Tomasz, and Andrea Ehrmann. “Magnetic Elements for Neuromorphic
    Computing.” <i>Molecules</i> 25, no. 11 (2020). <a href="https://doi.org/10.3390/molecules25112550">https://doi.org/10.3390/molecules25112550</a>.
  ieee: T. Blachowicz and A. Ehrmann, “Magnetic Elements for Neuromorphic Computing,”
    <i>Molecules</i>, vol. 25, no. 11, 2020.
  mla: Blachowicz, Tomasz, and Andrea Ehrmann. “Magnetic Elements for Neuromorphic
    Computing.” <i>Molecules</i>, vol. 25, no. 11, 2550, 2020, doi:<a href="https://doi.org/10.3390/molecules25112550">10.3390/molecules25112550</a>.
  short: T. Blachowicz, A. Ehrmann, Molecules 25 (2020).
date_created: 2021-01-03T16:40:37Z
date_updated: 2026-03-17T15:29:32Z
department:
- _id: '103'
doi: 10.3390/molecules25112550
file:
- access_level: open_access
  content_type: application/pdf
  creator: aehrmann
  date_created: 2021-01-03T16:40:04Z
  date_updated: 2021-01-03T16:40:04Z
  file_id: '663'
  file_name: _2020_Blachowicz_Molecules25_2550_v2.pdf
  file_size: 5784324
  relation: main_file
  success: 1
file_date_updated: 2021-01-03T16:40:04Z
funded_apc: '1'
has_accepted_license: '1'
intvolume: '        25'
issue: '11'
keyword:
- neuromorphic computing
- adaptive computing
- cognitive computing
- magnetism
- micromagnetic simulations
- magnetic nanoparticles
- neural network
language:
- iso: eng
main_file_link:
- open_access: '1'
oa: '1'
publication: Molecules
publication_identifier:
  issn:
  - 1420-3049
publication_status: published
quality_controlled: '1'
status: public
title: Magnetic Elements for Neuromorphic Computing
type: journal_article
urn: urn:nbn:de:hbz:bi10-6622
user_id: '243110'
volume: 25
year: '2020'
...