13 Publikationen

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  • [13]
    2023 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2982070
    Chan, R.K.-W., Penquitt, S., & Gottschalk, H., 2023. LU-Net: Invertible Neural Networks Based on Matrix Factorization. In 2023 International Joint Conference on Neural Networks (IJCNN). Piscataway, NJ: IEEE, pp. 1-10.
    PUB | DOI
     
  • [12]
    2023 | Zeitschriftenaufsatz | E-Veröff. vor dem Druck | PUB-ID: 2968966
    Chan, R.K.-W., et al., 2023. What should AI see? Using the public’s opinion to determine the perception of an AI. AI and Ethics.
    PUB | DOI | Download (ext.) | arXiv | Preprint
     
  • [11]
    2023 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2969466
    Maag, K., et al., 2023. Two Video Data Sets for Tracking and Retrieval of Out of Distribution Objects. In L. Wang, et al., eds. Computer Vision – ACCV 2022. 16th Asian Conference on Computer Vision, Macao, China, December 4–8, 2022, Proceedings, Part V. Lecture Notes in Computer Science. no.13845 Cham: Springer Nature Switzerland, pp. 476-494.
    PUB | DOI | Download (ext.)
     
  • [10]
    2022 | Dissertation | Veröffentlicht | PUB-ID: 2968878
    Chan, R.K.-W., 2022. Detecting Anything Overlooked in Semantic Segmentation, Bergische Universität Wuppertal.
    PUB | DOI | Download (ext.)
     
  • [9]
    2022 | Sammelwerksbeitrag | Veröffentlicht | PUB-ID: 2968876
    Chan, R.K.-W., et al., 2022. Detecting and Learning the Unknown in Semantic Segmentation. In T. Fingscheidt, H. Gottschalk, & S. Houben, eds. Deep Neural Networks and Data for Automated Driving. Robustness, Uncertainty Quantification, and Insights Towards Safety. Cham: Springer International Publishing, pp. 277-313.
    PUB | DOI
     
  • [8]
    2021 | Konferenzbeitrag | PUB-ID: 2968879
    Chan, R.K.-W., et al., 2021. SegmentMeIfYouCan: A Benchmark for Anomaly Segmentation. In Proceedings of the Neural Information Processing Systems (NeurIPS) Track on Datasets and Benchmarks.
    PUB | Download (ext.) | arXiv
     
  • [7]
    2021 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2968881
    Brüggemann, D., et al., 2021. Software architecture for human- centered reliability assessment for neural networks in autonomous. In Proc. of the 11th IMA International Conference on Modelling in Industrial Maintenance and Reliability. Institute of Mathematics & its Applications.
    PUB | DOI
     
  • [6]
    2021 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2968880
    Chan, R.K.-W., Rottmann, M., & Gottschalk, H., 2021. Entropy Maximization and Meta Classification for Out-of-Distribution Detection in Semantic Segmentation. In 2021 IEEE/CVF International Conference on Computer Vision (ICCV). IEEE, pp. 5108-5117.
    PUB | DOI
     
  • [5]
    2020 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2968885
    Rottmann, M., et al., 2020. Detection of False Positive and False Negative Samples in Semantic Segmentation. In 2020 Design, Automation & Test in Europe Conference & Exhibition (DATE). IEEE, pp. 1351-1356.
    PUB | DOI
     
  • [4]
    2020 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2968884
    Rottmann, M., et al., 2020. Prediction Error Meta Classification in Semantic Segmentation: Detection via Aggregated Dispersion Measures of Softmax Probabilities. In 2020 International Joint Conference on Neural Networks (IJCNN). IEEE, pp. 1-9.
    PUB | DOI
     
  • [3]
    2020 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2968883
    Chan, R.K.-W., et al., 2020. Controlled False Negative Reduction of Minority Classes in Semantic Segmentation. In 2020 International Joint Conference on Neural Networks (IJCNN). IEEE, pp. 1-8.
    PUB | DOI
     
  • [2]
    2020 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2968882
    Chan, R.K.-W., et al., 2020. Application of Maximum Likelihood Decision Rules for Handling Class Imbalance in Semantic Segmentation. In P. Baraldi, F. D. Maio, & E. Zio, eds. Proceedings of the 30th European Safety and Reliability Conference and 15th Probabilistic Safety Assessment and Management Conference. Singapore: Research Publishing Services, pp. 3065-3072.
    PUB | DOI
     
  • [1]
    2019 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2968886
    Chan, R.K.-W., et al., 2019. The Ethical Dilemma When (Not) Setting up Cost-Based Decision Rules in Semantic Segmentation. In 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW). IEEE, pp. 1395-1403.
    PUB | DOI
     

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