National Technical University of Athens (NTUA)

The National Technical University of Athens (NTUA), is the oldest (founded in 1837) and most prestigious Engineering University in Greece with a large involvement and participation in research projects both in a National and European level. NTUA has been ranked at the 10th position among all the European Universities in terms of research funded by the EU and at the 17th position among all the research centers in Europe. In this project, the Laboratory of Photogrammetry, Signal Processing & Computer Vision (P-SP-CV Lab.) which performs research in spectral analysis, signal processing, machine learning and environmental applications, is involved. The laboratory is currently involved into 6 H2020 projects in the area of photonics, environmental analysis, 3D reconstruction, Cultural heritage and energy. The lab has developed hyper-spectral imaging tools and machine learning algorithms. Particularly, the lab has developed to name a few: (a) Artificial intelligence algorithm for processing thermal data under H2020 STOP-IT project, (b) Fusion of thermal with RGB data under (FP7-Inachus, and H2020 STOP-IT projects, (c) Hyper-spectral image data processing (H2020 Panoptis), (d) Photonics signal analysis for environmental monitoring (H2020 WATERSPY) (e) real-time signal adaptive/tracing algorithms from un-calibrated capturing sensors equipped with technologies that extract geolocations of the detected objects of interest (FP7-SCOVIS project).

Role in PHOOTONICS: NTUA will lead the development of the embedded adaptive signal processing subsystem and the employment of machine learning techniques, to increase the reliability of the PHOOTONICS device. Specifically, within WP6 the NTUA will utilize the state-of-the-art algorithms in noise removal, SNR ratio improvement and super resolution to enhance spatial discrimination and provide a more robust and efficient analysis of the hyperspectral information. Furthermore, NTUA will play a significant role in the technical specifications of the project and in the dissemination of the research results in the scientific community, through journal papers or conferences.

Consortium

© 2020 PHOOTONICS

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This project is an initiative of the Photonics Public Private Partnership www.photonics21.org and has received funding from the European Union's Horizon 2020 research and innovation programme under grant agreement no 871908.

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