Research output per year
Research output per year
Description
Source code and data for the paper:
Taira Giordani, Alessia Suprano, Emanuele Polino, Francesca Acanfora, Luca Innocenti, Alessandro Ferraro, Mauro Paternostro, Nicoló Spagnolo, and Fabio Sciarrino, Machine learning-based classification of vector vortex beams, Phys. Rev. Lett. 124, 160401, (2020).
Content:
Notebooks: Jupyer notebooks containing code and explanations to reproduce the results of the paper.
src. The notebooks use a number of supporting functions, which are all defined here.
Data: Contains the datasets used in the notebooks.
Saved_CNN_models. Pre-trained CNNs used in the notebooks.
Taira Giordani, Alessia Suprano, Emanuele Polino, Francesca Acanfora, Luca Innocenti, Alessandro Ferraro, Mauro Paternostro, Nicoló Spagnolo, and Fabio Sciarrino, Machine learning-based classification of vector vortex beams, Phys. Rev. Lett. 124, 160401, (2020).
Content:
Notebooks: Jupyer notebooks containing code and explanations to reproduce the results of the paper.
src. The notebooks use a number of supporting functions, which are all defined here.
Data: Contains the datasets used in the notebooks.
Saved_CNN_models. Pre-trained CNNs used in the notebooks.
| Date made available | Aug 2020 |
|---|---|
| Publisher | Queen's University Belfast |
| Date of data production | 2020 |
Research output
- 1 Article
-
Machine learning-based classification of vector vortex beams
Giordani, T., Suprano, A., Polino, E., Acanfora, F., Innocenti, L., Ferraro, A., Paternostro, M., Spagnolo, N. & Sciarrino, F., 16 May 2020, In: Phys. Rev. Lett..Research output: Contribution to journal › Article › peer-review
Open AccessFile13 Citations (Scopus)100 Downloads (Pure)
Student Theses
-
Machine-learning-assisted state and gate engineering for quantum technologies
Author: Innocenti, L., Dec 2020Supervisor: Ferraro, A. (Supervisor) & Paternostro, M. (Supervisor)
Student thesis: Doctoral Thesis › Doctor of Philosophy
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