PUB - Publikationen an der Universität Bielefeld

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• [13]
  

  2023 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2982070

  Chan, R. K. - W., Penquitt, S., and Gottschalk, H. (2023). “LU-Net: Invertible Neural Networks Based on Matrix Factorization” in 2023 International Joint Conference on Neural Networks (IJCNN) (Piscataway, NJ: IEEE), 1-10.

  PUB | DOI
   
• [12]
  

  2023 | Zeitschriftenaufsatz | E-Veröff. vor dem Druck | PUB-ID: 2968966

  Chan, R. K. - W., Dardashti, R., Osinski, M., Rottmann, M., Brüggemann, D., Rücker, C., Schlicht, P., Hüger, F., Rummel, N., and Gottschalk, H. (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., Chan, R. K. - W., Uhlemeyer, S., Kowol, K., and Gottschalk, H. (2023). “Two Video Data Sets for Tracking and Retrieval of Out of Distribution Objects” in Computer Vision – ACCV 2022. 16th Asian Conference on Computer Vision, Macao, China, December 4–8, 2022, Proceedings, Part V, Wang, L., Gall, J., Chin, T. - J., Sato, I., and Chellappa, R. eds. Lecture Notes in Computer Science, vol. 13845, (Cham: Springer Nature Switzerland), 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., Uhlemeyer, S., Rottmann, M., and Gottschalk, H. (2022). “Detecting and Learning the Unknown in Semantic Segmentation” in Deep Neural Networks and Data for Automated Driving. Robustness, Uncertainty Quantification, and Insights Towards Safety, Fingscheidt, T., Gottschalk, H., and Houben, S. eds. (Cham: Springer International Publishing), 277-313.

  PUB | DOI
   
• [8]
  

  2021 | Konferenzbeitrag | PUB-ID: 2968879

  Chan, R. K. - W., Lis, K., Uhlemeyer, S., Blum, H., Honari, S., Siegwart, R., Fua, P., Salzmann, M., and Rottmann, M. (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., Chan, R. K. - W., Gottschalk, H., and Bracke, S. (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., and 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), 5108-5117.

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• [5]
  

  2020 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2968885

  Rottmann, M., Maag, K., Chan, R. K. - W., Huger, F., Schlicht, P., and Gottschalk, H. (2020). “Detection of False Positive and False Negative Samples in Semantic Segmentation” in 2020 Design, Automation & Test in Europe Conference & Exhibition (DATE) (IEEE), 1351-1356.

  PUB | DOI
   
• [4]
  

  2020 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2968884

  Rottmann, M., Colling, P., Paul Hack, T., Chan, R. K. - W., Huger, F., Schlicht, P., and Gottschalk, H. (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), 1-9.

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• [3]
  

  2020 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2968883

  Chan, R. K. - W., Rottmann, M., Huger, F., Schlicht, P., and Gottschalk, H. (2020). “Controlled False Negative Reduction of Minority Classes in Semantic Segmentation” in 2020 International Joint Conference on Neural Networks (IJCNN) (IEEE), 1-8.

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• [2]
  

  2020 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2968882

  Chan, R. K. - W., Rottmann, M., Gottschalk, H., Hüger, F., and Schlicht, P. (2020). “Application of Maximum Likelihood Decision Rules for Handling Class Imbalance in Semantic Segmentation” in Proceedings of the 30th European Safety and Reliability Conference and 15th Probabilistic Safety Assessment and Management Conference, Baraldi, P., Maio, F. D., and Zio, E. eds. (Singapore: Research Publishing Services), 3065-3072.

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• [1]
  

  2019 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2968886

  Chan, R. K. - W., Rottmann, M., Dardashti, R., Huger, F., Schlicht, P., and Gottschalk, H. (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), 1395-1403.

  PUB | DOI