| Issue |
EPJ Web Conf.
Volume 266, 2022
EOS Annual Meeting (EOSAM 2022)
|
|
|---|---|---|
| Article Number | 13029 | |
| Number of page(s) | 2 | |
| Section | Topical Meeting (TOM) 13- Advances and Applications of Optics and Photonics | |
| DOI | https://doi.org/10.1051/epjconf/202226613029 | |
| Published online | 13 October 2022 | |
https://doi.org/10.1051/epjconf/202226613029
Intelligent Optical Tweezers with deep neural network classifiers
1 Faculdade de Ciências da Universidade do Porto, Rua do Campo Alegre 687, 4169-007 Porto, Portugal
2 INESC TEC, Centre of Applied Photonics, Rua do Campo Alegre 687, 4169-007 Porto, Portugal
* e-mail: vicentevrocha.vvr@gmail.com
Published online: 13 October 2022
Optical tweezers use light to trap and manipulate mesoscopic scaled particles with high precision making them a useful tool in a plethora of natural sciences, with emphasis on biological applications. In principle, the Brownian-like dynamics reflect trapped particle properties making it a robust source of information. In this work, we exploit this information by plotting histogram based images of 250ms of position or displacement used as input to a Convolution Neural Network. Results of 2-fold stratified cross-validation show satisfying classifications between sizes or types of particles: Polystyrene and Polymethilmethacrylate thus highlighting the potential of CNN approaches in faster and non-invasive applications in intelligent opto and microfluidic devices using optical trapping tools.
© The Authors, published by EDP Sciences
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