18 Publikationen

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  • [18]
    2023 | Zeitschriftenaufsatz | Veröffentlicht | PUB-ID: 2979717
    Momber, A.W., et al., 2023. The exploration and annotation of large amounts of visual inspection data for protective coating systems on stationary marine steel structures. Ocean Engineering, 278: 114337.
    PUB | DOI | WoS
     
  • [17]
    2023 | Zeitschriftenaufsatz | E-Veröff. vor dem Druck | PUB-ID: 2968512
    Momber, A., et al., 2023. Eine Online-Plattform für die Verarbeitung digitaler visueller Daten zur Zustandsbeschreibung von Beschichtungssystemen an maritimen Stahlbauten. Stahlbau .
    PUB | DOI | WoS
     
  • [16]
    2022 | Zeitschriftenaufsatz | Veröffentlicht | PUB-ID: 2962701
    Momber, A.W., et al., 2022. Corrigendum to “A data-based model for condition monitoring and maintenance planning for protective coating systems for wind tower structures” [Renew. Energy 186 (2022) 957–973]. Renewable Energy , 188, p 1184.
    PUB | DOI | WoS
     
  • [15]
    2022 | Zeitschriftenaufsatz | Veröffentlicht | PUB-ID: 2960547
    Momber, A.W., et al., 2022. A data-based model for condition monitoring and maintenance planning for protective coating systems for wind tower structures. Renewable Energy.
    PUB | DOI
     
  • [14]
    2021 | Zeitschriftenaufsatz | E-Veröff. vor dem Druck | PUB-ID: 2960196
    Momber, A.W., et al., 2021. A Digital Twin concept for the prescriptive maintenance of protective coating systems on wind turbine structures. Wind Engineering, : 0309524X211060550.
    PUB | DOI | WoS
     
  • [13]
    2021 | Zeitschriftenaufsatz | Veröffentlicht | PUB-ID: 2956291
    Momber, A., et al., 2021. Digitalisierung und Verarbeitung von Sensordaten für die Zustandsbewertung von Oberflächenschutzsystemen stählerner Türme von Onshore-Windenergieanlagen. Stahlbau, 90(7), p 528-541.
    PUB | DOI | WoS
     
  • [12]
    2021 | Zeitschriftenaufsatz | Veröffentlicht | PUB-ID: 2950877 OA
    Möller, T., & Nattkemper, T.W., 2021. ALMI - A Generic Active Learning System for Computational Object Classification in Marine Observation Images. Sensors, 21(4): 1134.
    PUB | PDF | DOI | Download (ext.) | WoS | PubMed | Europe PMC
     
  • [11]
    2019 | Konferenzbeitrag | Im Druck | PUB-ID: 2937705
    Möller, T., Langenkämper, D., & Nattkemper, T.W., In Press. Wind turbine segmentation performing kNN-clustering on superpixel segmentations. In L. Bruzzone & F. Bovolo, eds. Image and Signal Processing for Remote Sensing XXV. Image and Signal Processing for Remote Sensing XXV. Proceedings. no.11155
    PUB
     
  • [10]
    2018 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2921040
    Möller, T., Nillsen, I., & Nattkemper, T.W., 2018. Tracking Sponge Size and Behaviour with Fixed Underwater Observatories. In Z. Zhang, et al., eds. Pattern Recognition and Information Forensics. ICPR 2018 International Workshops, CVAUI, IWCF, and MIPPSNA, Beijing, China, August 20-24, 2018, Revised Selected Papers. Lecture Notes in Computer Science. no.11188 Cham: Springer, pp. 45-54.
    PUB | DOI
     
  • [9]
    2017 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2915349
    Möller, T., Nilssen, I., & Nattkemper, T.W., 2017. Active learning for the classification of species in underwater images from a fixed observatory. In Proceedings of The IEEE International Conference on Computer Vision Workships (ICCVW). Piscataway, NJ: IEEE, pp. 2891-2897.
    PUB
     
  • [8]
    2017 | Kurzbeitrag Konferenz / Poster | Veröffentlicht | PUB-ID: 2908753 OA
    Osterloff, J., et al., 2017. Extracting Scalar Quantities from Underwater Images - a Toolbox for Image Data from Fixed Observatories. Presented at the Marine Imaging Workshop 2017, Kiel.
    PUB | PDF
     
  • [7]
    2016 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2904671
    Möller, T., Nilssen, I., & Nattkemper, T.W., 2016. Change Detection in Marine Observatory Image Streams using Bi-Domain Feature Clustering. In 2016 23rd International Conference on Pattern Recognition (ICPR). Piscataway, NJ: IEEE, pp. 793-798.
    PUB | DOI
     
  • [6]
    2016 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2906524
    Möller, T., Nilssen, I., & Nattkemper, T.W., 2016. Data-driven Long Term Change Analysis in Marine Observatory Image Streams. In 2016 ICPR 2nd Workshop on Computer Vision for Analysis of Underwater Imagery (CVAUI 2016) . Proceedings. Piscataway, NJ: IEEE, pp. 13-18.
    PUB
     
  • [5]
    2015 | Kurzbeitrag Konferenz / Poster | Veröffentlicht | PUB-ID: 2775951 OA
    Möller, T., et al., 2015. Change Detection in underwater time laps videos from stationary observatories. Presented at the GEOHAB, Salvador, Brazil.
    PUB | PDF
     
  • [4]
    2015 | Kurzbeitrag Konferenz / Poster | Veröffentlicht | PUB-ID: 2735538 OA
    Osterloff, J., et al., 2015. Computational analysis of spatial species distribution for integrated stationary environmental monitoring. Presented at the Geohab 2015, Salvador, Bahia, Brazil.
    PUB | PDF
     
  • [3]
    2014 | Kurzbeitrag Konferenz / Poster | Veröffentlicht | PUB-ID: 2656048 OA
    Möller, T., Nilssen, I., & Nattkemper, T.W., 2014. Introduction of image-based water transparency descriptors to quantify marine snow and turbidity features. A study with data from a stationary observatory. Presented at the MIW 2014 - Marine Imaging Workshop, Southampton.
    PUB | PDF
     
  • [2]
    2014 | Kurzbeitrag Konferenz / Poster | Veröffentlicht | PUB-ID: 2676320 OA
    Osterloff, J., et al., 2014. Automated Image based Biomass Quantification in Mesocosm Studies. Presented at the Geohab 2014, Lorne, Victoria, Australia.
    PUB | PDF
     
  • [1]
    2014 | Kurzbeitrag Konferenz / Poster | Veröffentlicht | PUB-ID: 2676334
    Möller, T., et al., 2014. Novelty detection in time lapse image data. Presented at the Geohab 2014, Lorne, Victoria, Australia.
    PUB
     

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