---
_id: '6235'
author:
- first_name: Marius
  full_name: Sangel, Marius
  id: '243822'
  last_name: Sangel
- first_name: Emilia
  full_name: Bensch, Emilia
  last_name: Bensch
- first_name: Hans
  full_name: Brandt-Pook, Hans
  id: '206531'
  last_name: Brandt-Pook
  orcid: 0009-0002-6668-2684
  orcid_put_code_url: https://api.orcid.org/v2.0/0009-0002-6668-2684/work/194297832
- first_name: Timo
  full_name: Röllke, Timo
  last_name: Röllke
- first_name: Cedric
  full_name: Markworth, Cedric
  last_name: Markworth
citation:
  alphadin: '<span style="font-variant:small-caps;">Sangel, Marius</span> ; <span
    style="font-variant:small-caps;">Bensch, Emilia</span> ; <span style="font-variant:small-caps;">Brandt-Pook,
    Hans</span> ; <span style="font-variant:small-caps;">Röllke, Timo</span> ; <span
    style="font-variant:small-caps;">Markworth, Cedric</span>: Automatisierte Erkennung
    von Störstoffen in Bioabfall mit maschinellem Lernen: Ansätze und Ergebnisse aus
    dem Projekt TRACES. In: <span style="font-variant:small-caps;">Gesellschaft für
    Informatik e.V.</span> (Hrsg.): <i>INFORMATIK 2025</i>. Bonn, 2025, S. 1363–1371'
  ama: 'Sangel M, Bensch E, Brandt-Pook H, Röllke T, Markworth C. Automatisierte Erkennung
    von Störstoffen in Bioabfall mit maschinellem Lernen: Ansätze und Ergebnisse aus
    dem Projekt TRACES. In: Gesellschaft für Informatik e.V., ed. <i>INFORMATIK 2025</i>.
    Bonn; 2025:1363-1371. doi:<a href="https://doi.org/10.18420/INF2025_121">10.18420/INF2025_121</a>'
  apa: 'Sangel, M., Bensch, E., Brandt-Pook, H., Röllke, T., &#38; Markworth, C. (2025).
    Automatisierte Erkennung von Störstoffen in Bioabfall mit maschinellem Lernen:
    Ansätze und Ergebnisse aus dem Projekt TRACES. In Gesellschaft für Informatik
    e.V. (Ed.), <i>INFORMATIK 2025</i> (pp. 1363–1371). Bonn. <a href="https://doi.org/10.18420/INF2025_121">https://doi.org/10.18420/INF2025_121</a>'
  bibtex: '@inproceedings{Sangel_Bensch_Brandt-Pook_Röllke_Markworth_2025, place={Bonn},
    title={Automatisierte Erkennung von Störstoffen in Bioabfall mit maschinellem
    Lernen: Ansätze und Ergebnisse aus dem Projekt TRACES}, DOI={<a href="https://doi.org/10.18420/INF2025_121">10.18420/INF2025_121</a>},
    number={366}, booktitle={INFORMATIK 2025}, author={Sangel, Marius and Bensch,
    Emilia and Brandt-Pook, Hans and Röllke, Timo and Markworth, Cedric}, editor={Gesellschaft
    für Informatik e.V.Editor}, year={2025}, pages={1363–1371} }'
  chicago: 'Sangel, Marius, Emilia Bensch, Hans Brandt-Pook, Timo Röllke, and Cedric
    Markworth. “Automatisierte Erkennung von Störstoffen in Bioabfall mit maschinellem
    Lernen: Ansätze und Ergebnisse aus dem Projekt TRACES.” In <i>INFORMATIK 2025</i>,
    edited by Gesellschaft für Informatik e.V., 1363–71. Bonn, 2025. <a href="https://doi.org/10.18420/INF2025_121">https://doi.org/10.18420/INF2025_121</a>.'
  ieee: 'M. Sangel, E. Bensch, H. Brandt-Pook, T. Röllke, and C. Markworth, “Automatisierte
    Erkennung von Störstoffen in Bioabfall mit maschinellem Lernen: Ansätze und Ergebnisse
    aus dem Projekt TRACES,” in <i>INFORMATIK 2025</i>, Potsdam, 2025, no. 366, pp.
    1363–1371.'
  mla: 'Sangel, Marius, et al. “Automatisierte Erkennung von Störstoffen in Bioabfall
    mit maschinellem Lernen: Ansätze und Ergebnisse aus dem Projekt TRACES.” <i>INFORMATIK
    2025</i>, edited by Gesellschaft für Informatik e.V., no. 366, 2025, pp. 1363–71,
    doi:<a href="https://doi.org/10.18420/INF2025_121">10.18420/INF2025_121</a>.'
  short: 'M. Sangel, E. Bensch, H. Brandt-Pook, T. Röllke, C. Markworth, in: Gesellschaft
    für Informatik e.V. (Ed.), INFORMATIK 2025, Bonn, 2025, pp. 1363–1371.'
conference:
  end_date: 2025-09-19
  location: Potsdam
  name: INFORMATIKFESTIVAL 2025
  start_date: 2025-09-16
corporate_editor:
- Gesellschaft für Informatik e.V.
date_created: 2025-10-15T07:05:27Z
date_updated: 2026-03-17T15:29:27Z
department:
- _id: 4b2dc5c9-bee3-11eb-b75f-ecc80f94fb21
doi: 10.18420/INF2025_121
file:
- access_level: open_access
  content_type: application/pdf
  creator: msangel1
  date_created: 2025-10-15T07:02:12Z
  date_updated: 2025-10-15T07:02:12Z
  file_id: '6236'
  file_name: Automatisierte Erkennung von Störstoffen in Bioabfall mit maschinellem
    Lernen Ansätze und Ergebnisse aus dem Projekt TRACES.pdf
  file_size: 14374281
  relation: main_file
  success: 1
file_date_updated: 2025-10-15T07:02:12Z
has_accepted_license: '1'
issue: '366'
keyword:
- Machine Learning
- Computer Vision
- Instance Segmentation
- CNNs
- YOLACT
- Data Augmentation
- Waste Classification
- Trash Detection
- Biowaste Analysis
language:
- iso: ger
main_file_link:
- open_access: '1'
oa: '1'
page: 1363-1371
place: Bonn
project:
- _id: f432a2ee-bceb-11ed-a251-a83585c5074d
  name: Institute for Data Science Solutions
publication: INFORMATIK 2025
publication_identifier:
  unknown:
  - 2944-7682
publication_status: epub_ahead
quality_controlled: '1'
status: public
title: 'Automatisierte Erkennung von Störstoffen in Bioabfall mit maschinellem Lernen:
  Ansätze und Ergebnisse aus dem Projekt TRACES'
tmp:
  image: /images/cc_by_sa.png
  legal_code_url: https://creativecommons.org/licenses/by-sa/4.0/legalcode
  name: Creative Commons Attribution-ShareAlike 4.0 International Public License (CC
    BY-SA 4.0)
  short: CC BY-SA (4.0)
type: conference
urn: urn:nbn:de:hbz:bi10-62353
user_id: '243822'
year: '2025'
...
---
_id: '4881'
article_type: original
author:
- first_name: Frauke
  full_name: Wiegraebe, Frauke
  last_name: Wiegraebe
- first_name: Marleen
  full_name: Schönbeck, Marleen
  last_name: Schönbeck
- first_name: Paul
  full_name: Wunderlich, Paul
  last_name: Wunderlich
- first_name: Annette
  full_name: Nauerth, Annette
  id: '33965'
  last_name: Nauerth
  orcid: 0009-0006-8407-3136
  orcid_put_code_url: https://api.orcid.org/v2.0/0009-0006-8407-3136/work/165894265
- first_name: Helene
  full_name: Dörksen, Helene
  last_name: Dörksen
citation:
  alphadin: '<span style="font-variant:small-caps;">Wiegraebe, Frauke</span> ; <span
    style="font-variant:small-caps;">Schönbeck, Marleen</span> ; <span style="font-variant:small-caps;">Wunderlich,
    Paul</span> ; <span style="font-variant:small-caps;">Nauerth, Annette</span> ;
    <span style="font-variant:small-caps;">Dörksen, Helene</span>: KI-basiertes Unterstützungstool
    für pflegende Erwerbstätige. In: <i>Pflege und Gesellschaft</i> Bd. 3, BeltzJuventa
    (2024), S. 271–285'
  ama: Wiegraebe F, Schönbeck M, Wunderlich P, Nauerth A, Dörksen H. KI-basiertes
    Unterstützungstool für pflegende Erwerbstätige. <i>Pflege und Gesellschaft</i>.
    2024;3:271-285. doi:<a href="https://doi.org/10.3262/P&#38;G2403271">10.3262/P&#38;G2403271</a>
  apa: Wiegraebe, F., Schönbeck, M., Wunderlich, P., Nauerth, A., &#38; Dörksen, H.
    (2024). KI-basiertes Unterstützungstool für pflegende Erwerbstätige. <i>Pflege
    und Gesellschaft</i>, <i>3</i>, 271–285. <a href="https://doi.org/10.3262/P&#38;G2403271">https://doi.org/10.3262/P&#38;G2403271</a>
  bibtex: '@article{Wiegraebe_Schönbeck_Wunderlich_Nauerth_Dörksen_2024, title={KI-basiertes
    Unterstützungstool für pflegende Erwerbstätige}, volume={3}, DOI={<a href="https://doi.org/10.3262/P&#38;G2403271">10.3262/P&#38;G2403271</a>},
    journal={Pflege und Gesellschaft}, publisher={BeltzJuventa}, author={Wiegraebe,
    Frauke and Schönbeck, Marleen and Wunderlich, Paul and Nauerth, Annette and Dörksen,
    Helene}, year={2024}, pages={271–285} }'
  chicago: 'Wiegraebe, Frauke, Marleen Schönbeck, Paul Wunderlich, Annette Nauerth,
    and Helene Dörksen. “KI-basiertes Unterstützungstool für pflegende Erwerbstätige.”
    <i>Pflege und Gesellschaft</i> 3 (2024): 271–85. <a href="https://doi.org/10.3262/P&#38;G2403271">https://doi.org/10.3262/P&#38;G2403271</a>.'
  ieee: F. Wiegraebe, M. Schönbeck, P. Wunderlich, A. Nauerth, and H. Dörksen, “KI-basiertes
    Unterstützungstool für pflegende Erwerbstätige,” <i>Pflege und Gesellschaft</i>,
    vol. 3, pp. 271–285, 2024.
  mla: Wiegraebe, Frauke, et al. “KI-basiertes Unterstützungstool für pflegende Erwerbstätige.”
    <i>Pflege und Gesellschaft</i>, vol. 3, BeltzJuventa, 2024, pp. 271–85, doi:<a
    href="https://doi.org/10.3262/P&#38;G2403271">10.3262/P&#38;G2403271</a>.
  short: F. Wiegraebe, M. Schönbeck, P. Wunderlich, A. Nauerth, H. Dörksen, Pflege
    und Gesellschaft 3 (2024) 271–285.
date_created: 2024-08-20T16:06:49Z
date_updated: 2026-03-17T15:29:08Z
department:
- _id: 4b342258-bee3-11eb-b75f-c9bf9d645214
doi: 10.3262/P&G2403271
intvolume: '         3'
keyword:
- Digital care support tool
- caring workforce
- interdisciplinarity
- AI application
- machine learning
- user orientation
language:
- iso: ger
page: 271-285
publication: Pflege und Gesellschaft
publication_identifier:
  issn:
  - 1430-9653
publication_status: published
publisher: BeltzJuventa
quality_controlled: '1'
research_group:
- _id: f025f82c-c221-11ec-90a2-d82e18d06cb8
  name: CareTech OWL - Zentrum für Gesundheit, Soziales und Technologie
status: public
title: KI-basiertes Unterstützungstool für pflegende Erwerbstätige
type: journal_article
user_id: '220548'
volume: 3
year: '2024'
...
---
_id: '4392'
alternative_id:
- '5468'
author:
- first_name: Felix
  full_name: Grumbach, Felix
  id: '243801'
  last_name: Grumbach
  orcid: 0000-0001-6348-7897
  orcid_put_code_url: https://api.orcid.org/v2.0/0000-0001-6348-7897/work/156390666
citation:
  alphadin: '<span style="font-variant:small-caps;">Grumbach, Felix</span>: <i>Feldsynchrone
    Ablaufplanung dynamischer Fertigungsprozesse mit Techniken des maschinellen Lernens
    [kumulative Dissertation]</i>. Bernburg : Universitäts- und Landesbibliothek Sachsen-Anhalt,
    2024'
  ama: 'Grumbach F. <i>Feldsynchrone Ablaufplanung dynamischer Fertigungsprozesse
    mit Techniken des maschinellen Lernens [kumulative Dissertation]</i>. Bernburg:
    Universitäts- und Landesbibliothek Sachsen-Anhalt; 2024. doi:<a href="https://doi.org/10.25673/115290">10.25673/115290</a>'
  apa: 'Grumbach, F. (2024). <i>Feldsynchrone Ablaufplanung dynamischer Fertigungsprozesse
    mit Techniken des maschinellen Lernens [kumulative Dissertation]</i>. Bernburg:
    Universitäts- und Landesbibliothek Sachsen-Anhalt. <a href="https://doi.org/10.25673/115290">https://doi.org/10.25673/115290</a>'
  bibtex: '@book{Grumbach_2024, place={Bernburg}, title={Feldsynchrone Ablaufplanung
    dynamischer Fertigungsprozesse mit Techniken des maschinellen Lernens [kumulative
    Dissertation]}, DOI={<a href="https://doi.org/10.25673/115290">10.25673/115290</a>},
    publisher={Universitäts- und Landesbibliothek Sachsen-Anhalt}, author={Grumbach,
    Felix}, year={2024} }'
  chicago: 'Grumbach, Felix. <i>Feldsynchrone Ablaufplanung dynamischer Fertigungsprozesse
    mit Techniken des maschinellen Lernens [kumulative Dissertation]</i>. Bernburg:
    Universitäts- und Landesbibliothek Sachsen-Anhalt, 2024. <a href="https://doi.org/10.25673/115290">https://doi.org/10.25673/115290</a>.'
  ieee: 'F. Grumbach, <i>Feldsynchrone Ablaufplanung dynamischer Fertigungsprozesse
    mit Techniken des maschinellen Lernens [kumulative Dissertation]</i>. Bernburg:
    Universitäts- und Landesbibliothek Sachsen-Anhalt, 2024.'
  mla: Grumbach, Felix. <i>Feldsynchrone Ablaufplanung dynamischer Fertigungsprozesse
    mit Techniken des maschinellen Lernens [kumulative Dissertation]</i>. Universitäts-
    und Landesbibliothek Sachsen-Anhalt, 2024, doi:<a href="https://doi.org/10.25673/115290">10.25673/115290</a>.
  short: F. Grumbach, Feldsynchrone Ablaufplanung dynamischer Fertigungsprozesse mit
    Techniken des maschinellen Lernens [kumulative Dissertation], Universitäts- und
    Landesbibliothek Sachsen-Anhalt, Bernburg, 2024.
date_created: 2024-03-14T11:32:15Z
date_updated: 2026-03-17T15:29:00Z
doi: 10.25673/115290
file:
- access_level: open_access
  content_type: application/pdf
  creator: fgrumbach1
  date_created: 2024-03-14T11:32:13Z
  date_updated: 2024-03-14T11:32:13Z
  file_id: '4393'
  file_name: Diss_FGrumbach_2024_Final.pdf
  file_size: 7859995
  relation: main_file
  success: 1
file_date_updated: 2024-03-14T11:32:13Z
has_accepted_license: '1'
keyword:
- Produktionsplanung und -steuerung
- Operations Research
- Machine Learning
- Reinforcement Learning
language:
- iso: ger
main_file_link:
- open_access: '1'
  url: http://dx.doi.org/10.25673/115290
oa: '1'
place: Bernburg
publication_identifier:
  eisbn:
  - 978-3-96057-174-2
publication_status: published
publisher: Universitäts- und Landesbibliothek Sachsen-Anhalt
status: public
supervisor:
- first_name: Sebastian
  full_name: Trojahn, Sebastian
  last_name: Trojahn
title: Feldsynchrone Ablaufplanung dynamischer Fertigungsprozesse mit Techniken des
  maschinellen Lernens [kumulative Dissertation]
tmp:
  image: /images/cc_by.png
  legal_code_url: https://creativecommons.org/licenses/by/4.0/legalcode
  name: Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)
  short: CC BY (4.0)
type: dissertation
urn: urn:nbn:de:hbz:bi10-43927
user_id: '220548'
year: '2024'
...
---
_id: '4394'
author:
- first_name: Anna
  full_name: Müller, Anna
  last_name: Müller
- first_name: Felix
  full_name: Grumbach, Felix
  id: '243801'
  last_name: Grumbach
  orcid: 0000-0001-6348-7897
citation:
  alphadin: '<span style="font-variant:small-caps;">Müller, Anna</span> ; <span style="font-variant:small-caps;">Grumbach,
    Felix</span>: Predicting processing times in high mix low volume job shops. In:
    <span style="font-variant:small-caps;">Glistau, E.</span> ; <span style="font-variant:small-caps;">Trojahn,
    S.</span> (Hrsg.): <i>16th International Doctoral Students Workshop on Logistics,
    Supply Chain and Production Management</i> : Otto von Guericke University Library,
    Magdeburg, Germany, 2023'
  ama: 'Müller A, Grumbach F. Predicting processing times in high mix low volume job
    shops. In: Glistau E, Trojahn S, eds. <i>16th International Doctoral Students
    Workshop on Logistics, Supply Chain and Production Management</i>. Otto von Guericke
    University Library, Magdeburg, Germany; 2023. doi:<a href="https://doi.org/10.25673/103491">10.25673/103491</a>'
  apa: 'Müller, A., &#38; Grumbach, F. (2023). Predicting processing times in high
    mix low volume job shops. In E. Glistau &#38; S. Trojahn (Eds.), <i>16th International
    Doctoral Students Workshop on Logistics, Supply Chain and Production Management</i>.
    Magdeburg: Otto von Guericke University Library, Magdeburg, Germany. <a href="https://doi.org/10.25673/103491">https://doi.org/10.25673/103491</a>'
  bibtex: '@inproceedings{Müller_Grumbach_2023, title={Predicting processing times
    in high mix low volume job shops}, DOI={<a href="https://doi.org/10.25673/103491">10.25673/103491</a>},
    booktitle={16th International Doctoral Students Workshop on Logistics, Supply
    Chain and Production Management}, publisher={Otto von Guericke University Library,
    Magdeburg, Germany}, author={Müller, Anna and Grumbach, Felix}, editor={Glistau,
    Elke and Trojahn, SebastianEditors}, year={2023} }'
  chicago: Müller, Anna, and Felix Grumbach. “Predicting Processing Times in High
    Mix Low Volume Job Shops.” In <i>16th International Doctoral Students Workshop
    on Logistics, Supply Chain and Production Management</i>, edited by Elke Glistau
    and Sebastian Trojahn. Otto von Guericke University Library, Magdeburg, Germany,
    2023. <a href="https://doi.org/10.25673/103491">https://doi.org/10.25673/103491</a>.
  ieee: A. Müller and F. Grumbach, “Predicting processing times in high mix low volume
    job shops,” in <i>16th International Doctoral Students Workshop on Logistics,
    Supply Chain and Production Management</i>, Magdeburg, 2023.
  mla: Müller, Anna, and Felix Grumbach. “Predicting Processing Times in High Mix
    Low Volume Job Shops.” <i>16th International Doctoral Students Workshop on Logistics,
    Supply Chain and Production Management</i>, edited by Elke Glistau and Sebastian
    Trojahn, Otto von Guericke University Library, Magdeburg, Germany, 2023, doi:<a
    href="https://doi.org/10.25673/103491">10.25673/103491</a>.
  short: 'A. Müller, F. Grumbach, in: E. Glistau, S. Trojahn (Eds.), 16th International
    Doctoral Students Workshop on Logistics, Supply Chain and Production Management,
    Otto von Guericke University Library, Magdeburg, Germany, 2023.'
conference:
  end_date: 20.06.2023
  location: Magdeburg
  name: 16th International Doctoral Students Workshops on Logistics, Supply Chain
    and Production Management
  start_date: 20.06.2023
date_created: 2024-03-14T11:37:12Z
date_updated: 2026-03-17T15:29:00Z
doi: 10.25673/103491
editor:
- first_name: Elke
  full_name: Glistau, Elke
  last_name: Glistau
- first_name: Sebastian
  full_name: Trojahn, Sebastian
  last_name: Trojahn
keyword:
- Machine Learning
- Production scheduling
- time prediction
language:
- iso: eng
main_file_link:
- open_access: '1'
  url: https://opendata.uni-halle.de//handle/1981185920/105445
oa: '1'
publication: 16th International Doctoral Students Workshop on Logistics, Supply Chain
  and Production Management
publisher: Otto von Guericke University Library, Magdeburg, Germany
quality_controlled: '1'
status: public
title: Predicting processing times in high mix low volume job shops
type: conference
user_id: '220548'
year: '2023'
...
---
_id: '4206'
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/157718021
- first_name: Amanullah
  full_name: Amanullah, Amanullah
  last_name: Amanullah
- first_name: 'Kaushik '
  full_name: 'Roy, Kaushik '
  last_name: Roy
- first_name: 'Jeong-A '
  full_name: 'Lee, Jeong-A '
  last_name: Lee
- first_name: 'Son '
  full_name: 'Chul-Jun, Son '
  last_name: Chul-Jun
- 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;">Amanullah, Amanullah</span> ; <span style="font-variant:small-caps;">Roy,
    Kaushik </span> ; <span style="font-variant:small-caps;">Lee, Jeong-A </span>
    ; <span style="font-variant:small-caps;">Chul-Jun, Son </span> ; <span style="font-variant:small-caps;">Jungeblut,
    Thorsten</span>: A Hybrid Spiking-Convolutional Neural Network Approach for Advancing
    High-Quality Image Inpainting. In: , 2023'
  ama: 'Sanaullah S, Amanullah A, Roy K, Lee J-A, Chul-Jun S, Jungeblut T. A Hybrid
    Spiking-Convolutional Neural Network Approach for Advancing High-Quality Image
    Inpainting. In: ; 2023. doi:<a href="https://doi.org/10.5281/zenodo.10458019">10.5281/zenodo.10458019</a>'
  apa: Sanaullah, S., Amanullah, A., Roy, K., Lee, J.-A., Chul-Jun, S., &#38; Jungeblut,
    T. (2023). A Hybrid Spiking-Convolutional Neural Network Approach for Advancing
    High-Quality Image Inpainting. Presented at the International Conference on Computer
    Vision (ICCV) 2023, Paris France. <a href="https://doi.org/10.5281/zenodo.10458019">https://doi.org/10.5281/zenodo.10458019</a>
  bibtex: '@inproceedings{Sanaullah_Amanullah_Roy_Lee_Chul-Jun_Jungeblut_2023, title={A
    Hybrid Spiking-Convolutional Neural Network Approach for Advancing High-Quality
    Image Inpainting}, DOI={<a href="https://doi.org/10.5281/zenodo.10458019">10.5281/zenodo.10458019</a>},
    author={Sanaullah, Sanaullah and Amanullah, Amanullah and Roy, Kaushik  and Lee,
    Jeong-A  and Chul-Jun, Son  and Jungeblut, Thorsten}, year={2023} }'
  chicago: Sanaullah, Sanaullah, Amanullah Amanullah, Kaushik  Roy, Jeong-A  Lee,
    Son  Chul-Jun, and Thorsten Jungeblut. “A Hybrid Spiking-Convolutional Neural
    Network Approach for Advancing High-Quality Image Inpainting,” 2023. <a href="https://doi.org/10.5281/zenodo.10458019">https://doi.org/10.5281/zenodo.10458019</a>.
  ieee: S. Sanaullah, A. Amanullah, K. Roy, J.-A. Lee, S. Chul-Jun, and T. Jungeblut,
    “A Hybrid Spiking-Convolutional Neural Network Approach for Advancing High-Quality
    Image Inpainting,” presented at the International Conference on Computer Vision
    (ICCV) 2023, Paris France, 2023.
  mla: Sanaullah, Sanaullah, et al. <i>A Hybrid Spiking-Convolutional Neural Network
    Approach for Advancing High-Quality Image Inpainting</i>. 2023, doi:<a href="https://doi.org/10.5281/zenodo.10458019">10.5281/zenodo.10458019</a>.
  short: 'S. Sanaullah, A. Amanullah, K. Roy, J.-A. Lee, S. Chul-Jun, T. Jungeblut,
    in: 2023.'
conference:
  end_date: 2023-10-6
  location: Paris France
  name: International Conference on Computer Vision (ICCV) 2023
  start_date: 2023-10-2
date_created: 2024-01-04T13:04:42Z
date_updated: 2026-03-17T15:28:57Z
doi: 10.5281/zenodo.10458019
external_id:
  zenodo:
  - 10.5281/zenodo.10458018
keyword:
- hybrid SC-NN
- SNN
- CNN
- Machine Learning
language:
- iso: eng
main_file_link:
- open_access: '1'
  url: https://www.researchgate.net/publication/377117919_A_Hybrid_Spiking-Convolutional_Neural_Network_Approach_for_Advancing_High-Quality_Image_Inpainting
oa: '1'
project:
- _id: beb248c8-cd75-11ed-b77c-e432b4711f7b
  name: Institut für Systemdynamik und Mechatronik
publication_status: published
status: public
title: A Hybrid Spiking-Convolutional Neural Network Approach for Advancing High-Quality
  Image Inpainting
type: conference_abstract
user_id: '242294'
year: '2023'
...
---
_id: '4207'
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/157718026
- 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;">Jungeblut, Thorsten</span>: Analysis of
    MR Images for Early and Accurate Detection of Brain Tumor using Resource Efficient
    Simulator Brain Analysis. In: . New York USA, 2023'
  ama: 'Sanaullah S, Jungeblut T. Analysis of MR Images for Early and Accurate Detection
    of Brain Tumor using Resource Efficient Simulator Brain Analysis. In: New York
    USA; 2023. doi:<a href="https://doi.org/10.5281/zenodo.10457930">10.5281/zenodo.10457930</a>'
  apa: Sanaullah, S., &#38; Jungeblut, T. (2023). Analysis of MR Images for Early
    and Accurate Detection of Brain Tumor using Resource Efficient Simulator Brain
    Analysis. Presented at the 19th International Conference on Machine Learning and
    Data Mining MLDM, New York USA. <a href="https://doi.org/10.5281/zenodo.10457930">https://doi.org/10.5281/zenodo.10457930</a>
  bibtex: '@inproceedings{Sanaullah_Jungeblut_2023, place={New York USA}, title={Analysis
    of MR Images for Early and Accurate Detection of Brain Tumor using Resource Efficient
    Simulator Brain Analysis}, DOI={<a href="https://doi.org/10.5281/zenodo.10457930">10.5281/zenodo.10457930</a>},
    author={Sanaullah, Sanaullah and Jungeblut, Thorsten}, year={2023} }'
  chicago: Sanaullah, Sanaullah, and Thorsten Jungeblut. “Analysis of MR Images for
    Early and Accurate Detection of Brain Tumor Using Resource Efficient Simulator
    Brain Analysis.” New York USA, 2023. <a href="https://doi.org/10.5281/zenodo.10457930">https://doi.org/10.5281/zenodo.10457930</a>.
  ieee: S. Sanaullah and T. Jungeblut, “Analysis of MR Images for Early and Accurate
    Detection of Brain Tumor using Resource Efficient Simulator Brain Analysis,” presented
    at the 19th International Conference on Machine Learning and Data Mining MLDM,
    New York USA, 2023.
  mla: Sanaullah, Sanaullah, and Thorsten Jungeblut. <i>Analysis of MR Images for
    Early and Accurate Detection of Brain Tumor Using Resource Efficient Simulator
    Brain Analysis</i>. 2023, doi:<a href="https://doi.org/10.5281/zenodo.10457930">10.5281/zenodo.10457930</a>.
  short: 'S. Sanaullah, T. Jungeblut, in: New York USA, 2023.'
conference:
  end_date: 2023-07-14
  location: New York USA
  name: 19th International Conference on Machine Learning and Data Mining MLDM
  start_date: 2023-07-13
date_created: 2024-01-04T13:06:32Z
date_updated: 2026-03-17T15:28:57Z
doi: 10.5281/zenodo.10457930
external_id:
  zenodo:
  - 10.5281/zenodo.10457929
keyword:
- Brain Analysis
- Machine Learning
- Simulator
- Runtime Simulator
language:
- iso: eng
main_file_link:
- open_access: '1'
  url: https://www.researchgate.net/publication/377117079_Analysis_of_MR_Images_for_Early_and_Accurate_Detection_of_Brain_Tumor_using_Resource_Efficient_Simulator_Brain_Analysis
oa: '1'
place: New York USA
project:
- _id: beb248c8-cd75-11ed-b77c-e432b4711f7b
  name: Institut für Systemdynamik und Mechatronik
publication_status: published
status: public
title: Analysis of MR Images for Early and Accurate Detection of Brain Tumor using
  Resource Efficient Simulator Brain Analysis
type: conference
user_id: '242294'
year: '2023'
...
---
_id: '3729'
author:
- first_name: Justus
  full_name: Kösters, Justus
  last_name: Kösters
- first_name: Marvin
  full_name: Schöne, Marvin
  id: '218388'
  last_name: Schöne
- first_name: Martin
  full_name: Kohlhase, Martin
  id: '226669'
  last_name: Kohlhase
  orcid: 0009-0002-9374-0720
citation:
  alphadin: '<span style="font-variant:small-caps;">Kösters, Justus</span> ; <span
    style="font-variant:small-caps;">Schöne, Marvin</span> ; <span style="font-variant:small-caps;">Kohlhase,
    Martin</span>: <i>Benchmarking of Machine Learning Models for Tabular Scarce Data</i>'
  ama: Kösters J, Schöne M, Kohlhase M. <i>Benchmarking of Machine Learning Models
    for Tabular Scarce Data</i>.
  apa: Kösters, J., Schöne, M., &#38; Kohlhase, M. (n.d.). <i>Benchmarking of Machine
    Learning Models for Tabular Scarce Data</i>.
  bibtex: '@book{Kösters_Schöne_Kohlhase, title={Benchmarking of Machine Learning
    Models for Tabular Scarce Data}, author={Kösters, Justus and Schöne, Marvin and
    Kohlhase, Martin} }'
  chicago: Kösters, Justus, Marvin Schöne, and Martin Kohlhase. <i>Benchmarking of
    Machine Learning Models for Tabular Scarce Data</i>, n.d.
  ieee: J. Kösters, M. Schöne, and M. Kohlhase, <i>Benchmarking of Machine Learning
    Models for Tabular Scarce Data</i>. .
  mla: Kösters, Justus, et al. <i>Benchmarking of Machine Learning Models for Tabular
    Scarce Data</i>.
  short: J. Kösters, M. Schöne, M. Kohlhase, Benchmarking of Machine Learning Models
    for Tabular Scarce Data, n.d.
date_created: 2023-11-16T13:43:06Z
date_updated: 2026-03-17T15:28:49Z
department:
- _id: '103'
file:
- access_level: open_access
  content_type: application/pdf
  creator: mschoene
  date_created: 2023-11-16T13:42:34Z
  date_updated: 2023-11-16T13:42:34Z
  file_id: '3730'
  file_name: BenchmarkingMlModelsScarceData_Koesters.pdf
  file_size: 329931
  relation: main_file
  success: 1
file_date_updated: 2023-11-16T13:42:34Z
has_accepted_license: '1'
keyword:
- tabular scarce data
- industrial design
- supervised machine learning models
language:
- iso: eng
main_file_link:
- open_access: '1'
oa: '1'
publication_status: submitted
status: public
title: Benchmarking of Machine Learning Models for Tabular Scarce Data
type: working_paper
urn: urn:nbn:de:hbz:bi10-37292
user_id: '220548'
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: '1799'
article_number: '2481'
author:
- first_name: Koenraad
  full_name: Vandevoorde, Koenraad
  id: '242844'
  last_name: Vandevoorde
- first_name: Lukas
  full_name: Vollenkemper, Lukas
  id: '245570'
  last_name: Vollenkemper
- first_name: Constanze
  full_name: Schwan, Constanze
  last_name: Schwan
- first_name: Martin
  full_name: Kohlhase, Martin
  id: '226669'
  last_name: Kohlhase
  orcid: 0009-0002-9374-0720
- first_name: Wolfram
  full_name: Schenck, Wolfram
  id: '224375'
  last_name: Schenck
  orcid: 0000-0003-3300-2048
citation:
  alphadin: '<span style="font-variant:small-caps;">Vandevoorde, Koenraad</span> ;
    <span style="font-variant:small-caps;">Vollenkemper, Lukas</span> ; <span style="font-variant:small-caps;">Schwan,
    Constanze</span> ; <span style="font-variant:small-caps;">Kohlhase, Martin</span>
    ; <span style="font-variant:small-caps;">Schenck, Wolfram</span>: Using Artificial
    Intelligence for Assistance Systems to Bring Motor Learning Principles into Real
    World Motor Tasks. In: <i>Sensors</i> Bd. 22, MDPI AG (2022), Nr. 7'
  ama: Vandevoorde K, Vollenkemper L, Schwan C, Kohlhase M, Schenck W. Using Artificial
    Intelligence for Assistance Systems to Bring Motor Learning Principles into Real
    World Motor Tasks. <i>Sensors</i>. 2022;22(7). doi:<a href="https://doi.org/10.3390/s22072481">10.3390/s22072481</a>
  apa: Vandevoorde, K., Vollenkemper, L., Schwan, C., Kohlhase, M., &#38; Schenck,
    W. (2022). Using Artificial Intelligence for Assistance Systems to Bring Motor
    Learning Principles into Real World Motor Tasks. <i>Sensors</i>, <i>22</i>(7).
    <a href="https://doi.org/10.3390/s22072481">https://doi.org/10.3390/s22072481</a>
  bibtex: '@article{Vandevoorde_Vollenkemper_Schwan_Kohlhase_Schenck_2022, title={Using
    Artificial Intelligence for Assistance Systems to Bring Motor Learning Principles
    into Real World Motor Tasks}, volume={22}, DOI={<a href="https://doi.org/10.3390/s22072481">10.3390/s22072481</a>},
    number={72481}, journal={Sensors}, publisher={MDPI AG}, author={Vandevoorde, Koenraad
    and Vollenkemper, Lukas and Schwan, Constanze and Kohlhase, Martin and Schenck,
    Wolfram}, year={2022} }'
  chicago: Vandevoorde, Koenraad, Lukas Vollenkemper, Constanze Schwan, Martin Kohlhase,
    and Wolfram Schenck. “Using Artificial Intelligence for Assistance Systems to
    Bring Motor Learning Principles into Real World Motor Tasks.” <i>Sensors</i> 22,
    no. 7 (2022). <a href="https://doi.org/10.3390/s22072481">https://doi.org/10.3390/s22072481</a>.
  ieee: K. Vandevoorde, L. Vollenkemper, C. Schwan, M. Kohlhase, and W. Schenck, “Using
    Artificial Intelligence for Assistance Systems to Bring Motor Learning Principles
    into Real World Motor Tasks,” <i>Sensors</i>, vol. 22, no. 7, 2022.
  mla: Vandevoorde, Koenraad, et al. “Using Artificial Intelligence for Assistance
    Systems to Bring Motor Learning Principles into Real World Motor Tasks.” <i>Sensors</i>,
    vol. 22, no. 7, 2481, MDPI AG, 2022, doi:<a href="https://doi.org/10.3390/s22072481">10.3390/s22072481</a>.
  short: K. Vandevoorde, L. Vollenkemper, C. Schwan, M. Kohlhase, W. Schenck, Sensors
    22 (2022).
date_created: 2022-04-04T10:08:43Z
date_updated: 2026-03-17T15:28:25Z
doi: 10.3390/s22072481
file:
- access_level: open_access
  content_type: application/pdf
  creator: kvandevoorde
  date_created: 2022-04-04T10:07:48Z
  date_updated: 2022-04-04T10:07:48Z
  file_id: '1800'
  file_name: sensors-22-02481-v3.pdf
  file_size: 2869767
  relation: main_file
  success: 1
file_date_updated: 2022-04-04T10:07:48Z
has_accepted_license: '1'
intvolume: '        22'
issue: '7'
keyword:
- motor learning
- motor skill learning
- assistance system
- artificial intelligence
- machine learning
- pose estimation
- action recognition
- human motion analysis
language:
- iso: eng
main_file_link:
- open_access: '1'
  url: https://www.mdpi.com/1424-8220/22/7/2481
oa: '1'
publication: Sensors
publication_identifier:
  eissn:
  - 1424-8220
publication_status: published
publisher: MDPI AG
quality_controlled: '1'
status: public
title: Using Artificial Intelligence for Assistance Systems to Bring Motor Learning
  Principles into Real World Motor Tasks
tmp:
  image: /images/cc_by.png
  legal_code_url: https://creativecommons.org/licenses/by/4.0/legalcode
  name: Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)
  short: CC BY (4.0)
type: journal_article
urn: urn:nbn:de:hbz:bi10-17992
user_id: '245590'
volume: 22
year: '2022'
...