15 Publikationen
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2024 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 3001612Shoeb, Y., Chan, Robin Kien-Wei, Schwalbe, G., Nowzad, A., Güney, F., and Gottschalk, H. “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). Los Alamitos: IEEE, 2024. IEEE Winter Conference on Applications of Computer Vision. 7381-7391.PUB | DOI | WoS
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2024 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2989164Velioglu, Riza, Chan, Robin Kien-Wei, and Hammer, Barbara. “FashionFail: Addressing Failure Cases in Fashion Object Detection and Segmentation”. 2024 International Joint Conference on Neural Networks (IJCNN). New York: Institute of Electrical and Electronics Engineers (IEEE), 2024. IEEE International Joint Conference on Neural Networks (IJCNN).PUB | DOI | WoS | arXiv
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2023 | Zeitschriftenaufsatz | Veröffentlicht | PUB-ID: 2968966Chan, Robin Kien-Wei, Dardashti, Radin, Osinski, Meike, Rottmann, Matthias, Brüggemann, Dominik, Rücker, Cilia, Schlicht, Peter, Hüger, Fabian, Rummel, Nikol, and Gottschalk, Hanno. “What should AI see? Using the public’s opinion to determine the perception of an AI”. AI and Ethics 3.4 (2023): 1381–1405.PUB | PDF | DOI | Download (ext.) | arXiv | Preprint
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2023 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2969466Maag, Kira, Chan, Robin Kien-Wei, Uhlemeyer, Svenja, Kowol, Kamil, and Gottschalk, Hanno. “Two Video Data Sets for Tracking and Retrieval of Out of Distribution Objects”. Computer Vision – ACCV 2022. 16th Asian Conference on Computer Vision, Macao, China, December 4–8, 2022, Proceedings, Part V. Ed. Lei Wang, Juergen Gall, Tat-Jun Chin, Imari Sato, and Rama Chellappa. Cham: Springer Nature Switzerland, 2023.Vol. 13845. Lecture Notes in Computer Science. 476-494.PUB | DOI | Download (ext.)
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2022 | Dissertation | Veröffentlicht | PUB-ID: 2968878Chan, Robin Kien-Wei. Detecting Anything Overlooked in Semantic Segmentation. Bergische Universität Wuppertal, 2022.PUB | DOI | Download (ext.)
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2022 | Sammelwerksbeitrag | Veröffentlicht | PUB-ID: 2968876Chan, Robin Kien-Wei, Uhlemeyer, Svenja, Rottmann, Matthias, and Gottschalk, Hanno. “Detecting and Learning the Unknown in Semantic Segmentation”. Deep Neural Networks and Data for Automated Driving. Robustness, Uncertainty Quantification, and Insights Towards Safety. Ed. Tim Fingscheidt, Hanno Gottschalk, and Sebastian Houben. Cham: Springer International Publishing, 2022. 277-313.PUB | DOI
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2021 | Konferenzbeitrag | PUB-ID: 2968879Chan, Robin Kien-Wei, Lis, Krzysztof, Uhlemeyer, Svenja, Blum, Hermann, Honari, Sina, Siegwart, Roland, Fua, Pascal, Salzmann, Mathieu, and Rottmann, Matthias. “SegmentMeIfYouCan: A Benchmark for Anomaly Segmentation”. Proceedings of the Neural Information Processing Systems (NeurIPS) Track on Datasets and Benchmarks. 2021.PUB | Download (ext.) | arXiv
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2021 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2968881Brüggemann, D, Chan, Robin Kien-Wei, Gottschalk, H, and Bracke, S. “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, 2021.PUB | DOI
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2021 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2968880Chan, Robin Kien-Wei, Rottmann, Matthias, and Gottschalk, Hanno. “Entropy Maximization and Meta Classification for Out-of-Distribution Detection in Semantic Segmentation”. 2021 IEEE/CVF International Conference on Computer Vision (ICCV). IEEE, 2021. 5108-5117.PUB | DOI
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2020 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2968885Rottmann, Matthias, Maag, Kira, Chan, Robin Kien-Wei, Huger, Fabian, Schlicht, Peter, and Gottschalk, Hanno. “Detection of False Positive and False Negative Samples in Semantic Segmentation”. 2020 Design, Automation & Test in Europe Conference & Exhibition (DATE). IEEE, 2020. 1351-1356.PUB | DOI
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2020 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2968884Rottmann, Matthias, Colling, Pascal, Paul Hack, Thomas, Chan, Robin Kien-Wei, Huger, Fabian, Schlicht, Peter, and Gottschalk, Hanno. “Prediction Error Meta Classification in Semantic Segmentation: Detection via Aggregated Dispersion Measures of Softmax Probabilities”. 2020 International Joint Conference on Neural Networks (IJCNN). IEEE, 2020. 1-9.PUB | DOI
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2020 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2968883Chan, Robin Kien-Wei, Rottmann, Matthias, Huger, Fabian, Schlicht, Peter, and Gottschalk, Hanno. “Controlled False Negative Reduction of Minority Classes in Semantic Segmentation”. 2020 International Joint Conference on Neural Networks (IJCNN). IEEE, 2020. 1-8.PUB | DOI
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2020 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2968882Chan, Robin Kien-Wei, Rottmann, Matthias, Gottschalk, Hanno, Hüger, Fabian, and Schlicht, Peter. “Application of Maximum Likelihood Decision Rules for Handling Class Imbalance in Semantic Segmentation”. Proceedings of the 30th European Safety and Reliability Conference and 15th Probabilistic Safety Assessment and Management Conference. Ed. Piero Baraldi, Francesco Di Maio, and Enrico Zio. Singapore: Research Publishing Services, 2020. 3065-3072.PUB | DOI
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2019 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2968886Chan, Robin Kien-Wei, Rottmann, Matthias, Dardashti, Radin, Huger, Fabian, Schlicht, Peter, and Gottschalk, Hanno. “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). IEEE, 2019. 1395-1403.PUB | DOI