PUB - Publikationen an der Universität Bielefeld

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• [15]
  

  2024 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 3001612

  Shoeb, Y., Chan, R. K. - W., Schwalbe, G., Nowzad, A., Güney, F., & Gottschalk, H. (2024). Have We Ever Encountered This Before? Retrieving Out-of-Distribution Road Obstacles from Driving Scenes. 2024 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV), IEEE Winter Conference on Applications of Computer Vision, 7381-7391. Los Alamitos: IEEE. https://doi.org/10.1109/WACV57701.2024.00723

  PUB | DOI | WoS
   
• [14]
  

  2024 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2989164

  Velioglu, R., Chan, R. K. - W., & Hammer, B. (2024). FashionFail: Addressing Failure Cases in Fashion Object Detection and Segmentation. 2024 International Joint Conference on Neural Networks (IJCNN), IEEE International Joint Conference on Neural Networks (IJCNN) New York: Institute of Electrical and Electronics Engineers (IEEE). https://doi.org/10.1109/IJCNN60899.2024.10651287

  PUB | DOI | WoS | arXiv
   
• [13]
  

  2023 | Zeitschriftenaufsatz | Veröffentlicht | PUB-ID: 2968966

  Chan, R. K. - W., Dardashti, R., Osinski, M., Rottmann, M., Brüggemann, D., Rücker, C., Schlicht, P., et al. (2023). What should AI see? Using the public’s opinion to determine the perception of an AI. AI and Ethics, 3(4), 1381–1405. https://doi.org/10.1007/s43681-022-00248-3

  PUB | PDF | DOI | Download (ext.) | arXiv | Preprint
   
• [12]
  

  2023 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2982070

  Chan, R. K. - W., Penquitt, S., & Gottschalk, H. (2023). LU-Net: Invertible Neural Networks Based on Matrix Factorization. 2023 International Joint Conference on Neural Networks (IJCNN), 1-10. Piscataway, NJ: IEEE. https://doi.org/10.1109/IJCNN54540.2023.10191440

  PUB | DOI
   
• [11]
  

  2023 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2969466

  Maag, K., Chan, R. K. - W., Uhlemeyer, S., Kowol, K., & Gottschalk, H. (2023). Two Video Data Sets for Tracking and Retrieval of Out of Distribution Objects. In L. Wang, J. Gall, T. - J. Chin, I. Sato, & R. Chellappa (Eds.), Lecture Notes in Computer Science: Vol. 13845. Computer Vision – ACCV 2022. 16th Asian Conference on Computer Vision, Macao, China, December 4–8, 2022, Proceedings, Part V (pp. 476-494). Cham: Springer Nature Switzerland. https://doi.org/10.1007/978-3-031-26348-4_28

  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. https://doi.org/10.25926/SPMR-X468

  PUB | DOI | Download (ext.)
   
• [9]
  

  2022 | Sammelwerksbeitrag | Veröffentlicht | PUB-ID: 2968876

  Chan, R. K. - W., Uhlemeyer, S., Rottmann, M., & Gottschalk, H. (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 (pp. 277-313). Cham: Springer International Publishing. https://doi.org/10.1007/978-3-031-01233-4_10

  PUB | DOI
   
• [8]
  

  2021 | Konferenzbeitrag | PUB-ID: 2968879

  Chan, R. K. - W., Lis, K., Uhlemeyer, S., Blum, H., Honari, S., Siegwart, R., Fua, P., et al. (2021). SegmentMeIfYouCan: A Benchmark for Anomaly Segmentation. 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., & Bracke, S. (2021). Software architecture for human- centered reliability assessment for neural networks in autonomous. Proc. of the 11th IMA International Conference on Modelling in Industrial Maintenance and Reliability Institute of Mathematics & its Applications. https://doi.org/10.19124/ima.2021.01.8

  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. 2021 IEEE/CVF International Conference on Computer Vision (ICCV), 5108-5117. IEEE. https://doi.org/10.1109/ICCV48922.2021.00508

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• [5]
  

  2020 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2968885

  Rottmann, M., Maag, K., Chan, R. K. - W., Huger, F., Schlicht, P., & Gottschalk, H. (2020). Detection of False Positive and False Negative Samples in Semantic Segmentation. 2020 Design, Automation & Test in Europe Conference & Exhibition (DATE), 1351-1356. IEEE. https://doi.org/10.23919/DATE48585.2020.9116288

  PUB | DOI
   
• [4]
  

  2020 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2968884

  Rottmann, M., Colling, P., Paul Hack, T., Chan, R. K. - W., Huger, F., Schlicht, P., & Gottschalk, H. (2020). Prediction Error Meta Classification in Semantic Segmentation: Detection via Aggregated Dispersion Measures of Softmax Probabilities. 2020 International Joint Conference on Neural Networks (IJCNN), 1-9. IEEE. https://doi.org/10.1109/IJCNN48605.2020.9206659

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• [3]
  

  2020 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2968883

  Chan, R. K. - W., Rottmann, M., Huger, F., Schlicht, P., & Gottschalk, H. (2020). Controlled False Negative Reduction of Minority Classes in Semantic Segmentation. 2020 International Joint Conference on Neural Networks (IJCNN), 1-8. IEEE. https://doi.org/10.1109/IJCNN48605.2020.9207104

  PUB | DOI
   
• [2]
  

  2020 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2968882

  Chan, R. K. - W., Rottmann, M., Gottschalk, H., Hüger, F., & Schlicht, P. (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 (pp. 3065-3072). Singapore: Research Publishing Services. https://doi.org/10.3850/978-981-14-8593-0_5748-cd

  PUB | DOI
   
• [1]
  

  2019 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2968886

  Chan, R. K. - W., Rottmann, M., Dardashti, R., Huger, F., Schlicht, P., & Gottschalk, H. (2019). The Ethical Dilemma When (Not) Setting up Cost-Based Decision Rules in Semantic Segmentation. 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW), 1395-1403. IEEE. https://doi.org/10.1109/CVPRW.2019.00180

  PUB | DOI