TR2022-110

Quantum Feature Extraction for THz Multi-Layer Imaging


Abstract:

A learning-based THz multi-layer imaging has been recently used for contactless three-dimensional (3D) positioning and encoding. We show a proof-of-concept demonstration of an emerging quantum machine learning (QML) framework to deal with depth variation, shadow effect, and double-sided content recognition, through an experimental validation.

 

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  •  Koike-Akino, T., Wang, P., Yamashita, G., Tsujita, W., Nakajima, M., "Quantum Feature Extraction for THz Multi-Layer Imaging", arXiv, July 2022.
    BibTeX arXiv
    • @article{Koike-Akino2022jul2,
    • author = {Koike-Akino, Toshiaki and Wang, Pu and Yamashita, Genki and Tsujita, Wataru and Nakajima, M.},
    • title = {Quantum Feature Extraction for THz Multi-Layer Imaging},
    • journal = {arXiv},
    • year = 2022,
    • month = jul,
    • url = {https://arxiv.org/abs/2207.09285}
    • }