PUB - Publikationen an der Universität Bielefeld

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• [15]
  

  2022 | Zeitschriftenaufsatz | Veröffentlicht | PUB-ID: 2966492

  Burfeid-Castellanos, A.M., et al., 2022. A Digital Light Microscopic Method for Diatom Surveys Using Embedded Acid-Cleaned Samples. Water, 14(20): 3332.

  PUB | PDF | DOI | Download (ext.) | WoS | Preprint
   
• [14]
  

  2022 | Bielefelder E-Dissertation | PUB-ID: 2965874

  Zurowietz, M., 2022. Large-Scale Marine Image Annotation in the Age of the Web and Deep Learning, Bielefeld: Universität Bielefeld.

  PUB | PDF | DOI
   
• [13]
  

  2022 | Zeitschriftenaufsatz | Veröffentlicht | PUB-ID: 2964509

  Schoening, T., et al., 2022. Making marine image data FAIR. Scientific data, 9(1): 414.

  PUB | DOI | WoS | PubMed | Europe PMC
   
• [12]
  

  2022 | Zeitschriftenaufsatz | Veröffentlicht | PUB-ID: 2964756

  Schoening, T., et al., 2022. Publisher Correction: Making marine image data FAIR. Scientific Data , 9(1): 445.

  PUB | DOI | WoS | PubMed | Europe PMC
   
• [11]
  

  2021 | Zeitschriftenaufsatz | Veröffentlicht | PUB-ID: 2959631

  Zurowietz, M., & Nattkemper, T.W., 2021. Current Trends and Future Directions of Large Scale Image and Video Annotation: Observations From Four Years of BIIGLE 2.0. Frontiers in Marine Science, 8: 760036.

  PUB | Dateien verfügbar | DOI | Download (ext.) | WoS
   
• [10]
  

  2021 | Zeitschriftenaufsatz | Veröffentlicht | PUB-ID: 2951226

  Wüllems, K., et al., 2021. Fast Visual Exploration of Mass Spectrometry Images with Interactive Dynamic Spectral Similarity Pseudocoloring. Scientific Reports, 11: 4606.

  PUB | PDF | DOI | Download (ext.) | WoS | PubMed | Europe PMC
   
• [9]
  

  2020 | Zeitschriftenaufsatz | Veröffentlicht | PUB-ID: 2945723

  Kloster, M., et al., 2020. Deep learning-based diatom taxonomy on virtual slides. Scientific Reports, 10(1): 14416.

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• [8]
  

  2020 | Zeitschriftenaufsatz | Veröffentlicht | PUB-ID: 2943901

  Zurowietz, M., & Nattkemper, T.W., 2020. An Interactive Visualization for Feature Localization in Deep Neural Networks. Frontiers in Artificial Intelligence - Machine Learning and Artificial Intelligence , 3: 49.

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• [7]
  

  2020 | Zeitschriftenaufsatz | Veröffentlicht | PUB-ID: 2945097

  Zurowietz, M., & Nattkemper, T.W., 2020. Unsupervised Knowledge Transfer for Object Detection in Marine Environmental Monitoring and Exploration. IEEE Access, 8.

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• [6]
  

  2020 | Zeitschriftenaufsatz | Veröffentlicht | PUB-ID: 2948381

  Langenkämper, D., et al., 2020. Corrigendum: BIIGLE 2.0 - Browsing and Annotating Large Marine Image Collections. Frontiers in Marine Science, 7: 617268.

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• [5]
  

  2019 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2935366

  Zurowietz, M., Langenkämper, D., & Nattkemper, T.W., 2019. BIIGLE2Go - A scalable image annotation system for easy deployment on cruises. In Proceedings of IEEE OCEANS 2019.

  PUB | DOI | Download (ext.)
   
• [4]
  

  2018 | Zeitschriftenaufsatz | Veröffentlicht | PUB-ID: 2932066

  Zurowietz, M., et al., 2018. MAIA - A machine learning assisted image annotation method for environmental monitoring and exploration . PLoS ONE, 13(11): e0207498.

  PUB | PDF | DOI | Download (ext.) | WoS | PubMed | Europe PMC
   
• [3]
  

  2017 | Zeitschriftenaufsatz | Veröffentlicht | PUB-ID: 2909190

  Langenkämper, D., et al., 2017. BIIGLE 2.0 - Browsing and Annotating Large Marine Image Collections. Frontiers in Marine Science, 4(March): 83.

  PUB | Dateien verfügbar | DOI | WoS
   
• [2]
  

  2014 | Kurzbeitrag Konferenz / Poster | Veröffentlicht | PUB-ID: 2690300

  Kölling, J., Zurowietz, M., & Nattkemper, T.W., 2014. Interactive Exploration of Spatial Distribution in Mass Spectrometry Imaging. Presented at the 4th Symposium on Biological Data Visualization (BioVis), Boston, MA, USA.

  PUB | Download (ext.)
   
• [1]
  

  2014 | Kurzbeitrag Konferenz / Poster | Veröffentlicht | PUB-ID: 2690322

  Kölling, J., Zurowietz, M., & Nattkemper, T.W., 2014. Interactive Exploration of Spatial Distribution in Mass Spectrometry Imaging. Presented at the 22nd Annual International Conference on Intelligent Systems for Molecular Biology (ISMB), Boston, MA, USA.

  PUB | Download (ext.)