Terahertz-Light Field Camera Prototyp
Light-field cameras record both the brightness and direction of the incident light rays. This spatiodirectional information can be post-processed for a dynamic focal point adjustment and 3-D imaging. Light-field has traditionally been a domain of visible light computational imaging. Our chair is leading the development of light-field methodologies for the THz spectrum, bringing new foundational understanding and hardware capabilities for bridging the terahertz gap.
Currently, we are building the first ever THz light-field camera prototype - which consists of a 3x3 super-array of lens coupled 1k-pixel THz CMOS cameras - in a single package. The CMOS camera chip is presented in the International Solid-State Circuits Conference (ISSCC) 2021. The figure shows the prototype of the light field array. The prototype serves as the hardware platform for the development of light-field based real-time THz 3-D imaging techniques.
Preliminary work:
- 2021
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In Proff, Heike, Editor, Making Connected Mobility Work Volume 119
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Michalik, David; Kohl, Per; Krause, Michael; Kummert, Anton; Meisen, Tobias
Synergiepotenziale von Virtual City Twins im Bereich automatisiertes Fahren ? Beschleunigung der technischen Entwicklung und
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KrishneGowda, Karthik; Rodríguez-Vázquez, Pedro; Lopacinski, Lukasz; Pfeiffer, Ullrich R.; Grass, Eckhard; Kraemer, Rolf
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Haussmann, N.; Zang, M.; Mease, R.; Schmuelling, B.; Clemens, M.; Bolten, M.
Towards Real-Time Magnetic Dosimetry Simulations for Inductive Charging Systems
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Meyes, Richard; Hütten, Nils; Meisen, Tobias
Transparent and Interpretable Failure Prediction of Sensor Time Series Data with Convolutional Neural Networks
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Goubeaud, Maxime; Joußen, Philipp; Gmyrek, Nicolla; Ghorban, Farzin; Schelkes, Lucas; Kummert, Anton
Using Variational Autoencoder to augment Sparse Time series Datasets
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Langer, Tristan; Meisen, Tobias
Visual Analytics for Industrial Sensor Data Analysis
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Langer, Tristan; Meisen, Tobias
Visual Analytics for Industrial Sensor Data Analysis
Proceedings of the 23rd International Conference on Enterprise Information Systems, Page 584—593
Publisher: SciTePress
2021ISBN: 978-989-758-509-8
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Langer, Tristan; Meisen, Tobias
Visual Analytics for Industrial Sensor Data Analysis
Proceedings of the 23rd International Conference on Enterprise Information Systems, Page 584—593
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Langer, Tristan; Meisen, Tobias
Visual Analytics for Industrial Sensor Data Analysis
Proceedings of the 23rd International Conference on Enterprise Information Systems, Page 584—593
Publisher: SciTePress
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Langer, Tristan; Meisen, Tobias
Visual Analytics for Industrial Sensor Data Analysis
Proceedings of the 23rd International Conference on Enterprise Information Systems, Page 584—593
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Bitter, Christian; Tercan, Hasan; Meisen, Tobias; Bodnar, Todd; Meisen, Philipp
When to Message: Investigating User Response Prediction with Machine Learning for Advertisement Emails
2021 4th International Conference on Artificial Intelligence for Industries (AI4I), Page 25—29
Publisher: IEEE
2021ISBN: 978-1-6654-3410-2
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Bitter, Christian; Tercan, Hasan; Meisen, Tobias; Bodnar, Todd; Meisen, Philipp
When to Message: Investigating User Response Prediction with Machine Learning for Advertisement Emails
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2021ISBN: 978-1-6654-3410-2
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Bitter, Christian; Tercan, Hasan; Meisen, Tobias; Bodnar, Todd; Meisen, Philipp
When to Message: Investigating User Response Prediction with Machine Learning for Advertisement Emails
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2021ISBN: 978-1-6654-3410-2
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Bitter, Christian; Tercan, Hasan; Meisen, Tobias; Bodnar, Todd; Meisen, Philipp
When to Message: Investigating User Response Prediction with Machine Learning for Advertisement Emails
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Publisher: IEEE
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Bitter, Christian; Tercan, Hasan; Meisen, Tobias; Bodnar, Todd; Meisen, Philipp
When to Message: Investigating User Response Prediction with Machine Learning for Advertisement Emails
2021 4th International Conference on Artificial Intelligence for Industries (AI4I), Page 25—29
Publisher: IEEE
2021ISBN: 978-1-6654-3410-2
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Goubeaud, Maxime; Joußen, Philipp; Gmyrek, Nicolla; Ghorban, Farzin; Kummert, Anton
White Noise Windows: Data Augmentation for Time Series
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Farooghi, Dena; Beitz, Bernard; Awad, Bayan; Tutsch, Dietmar
Zeitoptimierungsuntersuchungen f\"ur Algorithmen des maschinellen Lernens
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Farooghi, Dena; Beitz, Bernard; Awad, Bayan; Tutsch, Dietmar
Zeitoptimierungsuntersuchungen für Algorithmen des maschinellen Lernens
Echtzeit 2021, Boppard/Germany, GI, Page 123--131
Publisher: Springer-Vieweg
November 2021
