| Bibtype | Inproceedings |
|---|---|
| Bibkey | Wuestefeld/Weichert/2020a |
| Author | Wüstefeld, Konstantin and Weichert, Frank |
| Title | An Automated Rapid Test for Viral Nanoparticles Based on Spatiotemporal Deep Learning |
| Booktitle | 2020 IEEE Sensors |
| Pages | 1-4 |
| Abstract | The recent outbreak of the COVID-19 pandemic has
shown the importance of medical testing for an early detection of regional disease hot spots. The PAMONO sensor (Plasmon- Assisted Microscopy of Nano-Objects) can detect virus-like particles. It utilizes the surface plasmon resonance of particles attaching to an antibody coated gold plate to generate a stream of noisy images containing characteristic spatiotemporal signals. These signals are then analyzed via a deep neural network based architecture which targets a parameter-free usage on-site. It is able to detect individual (virus) particles within ten seconds and to reach a count exactness of higher than 80% in a minute. |
| Note | DOI=10.1109/SENSORS47125.2020.9278935 |
| Month | 10 |
| Year | 2020 |
| Projekt | SFB876-B2 |