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:
- 2020
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Burgdorf, Andreas; Pomp, André; Meisen, Tobias
Towards NLP-supported Semantic Data Management
arXiv preprint arXiv:2005.06916
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Burgdorf, Andreas; Pomp, André; Meisen, Tobias
Towards NLP-supported Semantic Data Management
arXiv preprint arXiv:2005.06916
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arXiv preprint arXiv:2005.06916
20202955.
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2020 International Conference on Computational Science and Computational Intelligence (CSCI), Page 504—509
Publisher: IEEE
2020ISBN: 978-1-7281-7624-6
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Scheiderer, Christian; Mosbach, Malte; Posada-Moreno, Andres Felipe; Meisen, Tobias
Transfer of Hierarchical Reinforcement Learning Structures for Robotic Manipulation Tasks
2020 International Conference on Computational Science and Computational Intelligence (CSCI), Page 504—509
Publisher: IEEE
2020ISBN: 978-1-7281-7624-6
2953.
Scheiderer, Christian; Mosbach, Malte; Posada-Moreno, Andres Felipe; Meisen, Tobias
Transfer of Hierarchical Reinforcement Learning Structures for Robotic Manipulation Tasks
2020 International Conference on Computational Science and Computational Intelligence (CSCI), Page 504—509
Publisher: IEEE
2020ISBN: 978-1-7281-7624-6
2952.
Scheiderer, Christian; Mosbach, Malte; Posada-Moreno, Andres Felipe; Meisen, Tobias
Transfer of Hierarchical Reinforcement Learning Structures for Robotic Manipulation Tasks
2020 International Conference on Computational Science and Computational Intelligence (CSCI), Page 504—509
Publisher: IEEE
2020ISBN: 978-1-7281-7624-6
2951.
Scheiderer, Christian; Mosbach, Malte; Posada-Moreno, Andres Felipe; Meisen, Tobias
Transfer of Hierarchical Reinforcement Learning Structures for Robotic Manipulation Tasks
2020 International Conference on Computational Science and Computational Intelligence (CSCI), Page 504—509
Publisher: IEEE
2020ISBN: 978-1-7281-7624-6
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Under the Hood of Neural Networks: Characterizing Learned Representations by Functional Neuron Populations and Network Ablations
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Meyes, Richard; Waubert-de-Puiseau, Constantin; Posada-Moreno, Andres; Meisen, Tobias
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Verbesserung der Nutzbarkeit von Open Data auf Basis eines semantischen Datenmarktplatzes
OKNRW - ONLINE BARCAMP 2020 Science-Track
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Verbesserung der Nutzbarkeit von Open Data auf Basis eines semantischen Datenmarktplatzes
OKNRW - ONLINE BARCAMP 2020 Science-Track
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Pomp, André; Paulus, Alexander; Burgdorf, Andreas; Meisen, Tobias
Verbesserung der Nutzbarkeit von Open Data auf Basis eines semantischen Datenmarktplatzes
OKNRW - ONLINE BARCAMP 2020 Science-Track
Page 14—15
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