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Augmenting Physiological Time Series Data: A Case Study for Sleep Apnea Detection.

, , , , , and . ECML/PKDD (3), volume 11908 of Lecture Notes in Computer Science, page 376-399. Springer, (2019)

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Learning from Higher-Layer Feature Visualizations., , , and . CoRR, (2019)Quantifying the Signal Quality of Low-cost Respiratory Effort Sensors for Sleep Apnea Monitoring., , and . HealthMedia@MM, page 3-11. ACM, (2018)Learning Realistic Patterns from Visually Unrealistic Stimuli: Generalization and Data Anonymization (Extended Abstract)., , , , , , , , , and 1 other author(s). IJCAI, page 5762-5766. ijcai.org, (2022)Learning Realistic Patterns from Visually Unrealistic Stimuli: Generalization and Data Anonymization., , , , , , , , , and 1 other author(s). J. Artif. Intell. Res., (2021)Data Mining for Patient Friendly Apnea Detection., , , , , and . IEEE Access, (2018)My Health Sensor, My Classifier - Adapting a Trained Classifier to Unlabeled End-User Data., , , , , , , , , and 1 other author(s). ACM Trans. Comput. Heal., 3 (4): 48:1-48:24 (2022)Modeling the Sofware Execution of CEP in DCEP-Sim., , , , and . DEBS, page 244-247. ACM, (2019)Using Under-trained Deep Ensembles to Learn Under Extreme Label Noise., , , , and . CoRR, (2020)Learning Realistic Patterns from Unrealistic Stimuli: Generalization and Data Anonymization., , , , , , , , , and 1 other author(s). CoRR, (2020)Cluster-Bildung und Partitionierung in Non-Standard-Datenbanksystemen., and . Grundlagen von Datenbanken, TR ECRC-92-13, page 45-50. (1992)