Multi Computer Vision‐Driven Testing Platform: Structural Reconstruction and Material Identification with Ultrabroadband Carbon Nanotube Imagers (Adv. Mater. Technol. 7/2025)
Carbon Nanotubes In article number 2401724, Yukio Kawano, Kou Li, and co-workers synergize material-identifying non-destructive inspections under non-invasive millimeter-wave–infrared irradiation with computer vision sensing. The system selectively extracts 3D structural information per constituent material from opaque complicated targets by carbon nanotube imagers.
Authors
- Minami Yamamoto
- N. Izumi (ORCID: https://orcid.org/0000-0003-1114-597X)
- Takeru Q. Suyama
- Yukio Kawano (ORCID: https://orcid.org/0000-0002-8456-2937)
- Yuya Kinoshita
- Hiroki Okawa
- Kou Li (ORCID: https://orcid.org/0000-0001-8756-819X)
- Tomoya Furukawa
- Masaaki Kosaka
- Daiki Sakai
- Satoshi Ikehata (ORCID: https://orcid.org/0000-0002-6061-7956)
- Miki Kubota
- Leo Takai
- Daiki Shikichi
- Ryoga Odawara
- Imari Sato
- Zhenyu Zhou (ORCID: https://orcid.org/0000-0001-9447-6023)
- Raito Ota
- Shota Wada
- Tomoki Nishi
- Yuto Aoshima
- Yuto Matsuzaki
Institutions
- Tokyo Institute of Technology (JP)
- National Institute of Informatics (JP)
- The Graduate University for Advanced Studies, SOKENDAI (JP)
- Kanagawa Industrial Technology Center (JP)
- Chuo University (JP)
Publication Details
- Journal
- Advanced Materials Technologies
- Published
- 2025-04-01
- DOI
- https://doi.org/10.1002/admt.202570040
- Primary Topic
- Sensor Technology and Measurement Systems
- Type
- article
- Field-Weighted Citation Impact
- 0.00