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Expertise Deep Learning, Computer Vision, Domain Adaptation, Generative Modeling Open Projects: Test-Time Domain Adaptation for Anomaly Detection: SiROP link for detailed information Han obtained her master's degree in Geomatic from the Federal Institute of Technology in Zürich (ETHZ). Before joining IMOS Lab - EPFL, she focused on computer vision with a particular interest in domain adaptation & style adaptation. During her Ph.D. study, she will explore more in the field of domain adaptation with its application in industrial data sets. ResearchDomain Adaptation Domain adaptation for anomaly detection & fault diagnosisGenerative Modeling Generative adversarial network, diffusion model, generative model-based domain adaptation & style adaptation Teaching & PhDCIVIL-332 Data Science for infrastructure condition monitoring Course BookCIVIL-426 Machine learning for predictive maintenance applications Course Book Awards ETH Medal Master's Thesis: Robust Object Detection with Efficient Labeled Data Factory 2022 Esri Young Scholar Award 2021 HoloInspect: A Mixed Reality BIM software on HoloLens 2021
Veuillez noter qu'il ne s'agit pas d'une liste complète des publications de cette personne. Elle inclut uniquement les travaux sémantiquement pertinents. Pour une liste complète, veuillez consulter Infoscience.