Lorenzo Riggi
Fluorescence Spectroscopy empowered by Data-Driven algorithms: A fast and cost-effective approach to Environmental Monitoring and Analysis.
Rel. Guido Perrone, Chiara Bellezza Prinsi. Politecnico di Torino, Corso di laurea magistrale in Ingegneria Elettronica (Electronic Engineering), 2024
|
PDF (Tesi_di_laurea)
- Tesi
Licenza: Creative Commons Attribution Non-commercial No Derivatives. Download (49MB) | Preview |
Abstract: |
Fluorescence Spectroscopy empowered by Data-Driven algorithms: A fast and cost-effective approach to Environmental Monitoring and Analysis |
---|---|
Relators: | Guido Perrone, Chiara Bellezza Prinsi |
Academic year: | 2023/24 |
Publication type: | Electronic |
Number of Pages: | 147 |
Subjects: | |
Corso di laurea: | Corso di laurea magistrale in Ingegneria Elettronica (Electronic Engineering) |
Classe di laurea: | New organization > Master science > LM-29 - ELECTRONIC ENGINEERING |
Aziende collaboratrici: | Politecnico di Torino |
URI: | http://webthesis.biblio.polito.it/id/eprint/30931 |
Modify record (reserved for operators) |