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Machine Learning Enabled Image Analysis of Time-Temperature Sensing Colloidal Arrays

DOI zum Zitieren der Version auf EPub Bayreuth: https://doi.org/10.15495/EPub_UBT_00007588
URN to cite this document: urn:nbn:de:bvb:703-epub-7588-1

Title data

Schöttle, Marius ; Tran, Thomas ; Oberhofer, Harald ; Retsch, Markus:
Machine Learning Enabled Image Analysis of Time-Temperature Sensing Colloidal Arrays.
In: Advanced Science. Vol. 10 (2023) Issue 8 . - 2205512.
ISSN 2198-3844
DOI der Verlagsversion: https://doi.org/10.1002/advs.202205512

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Name: Advanced Science - 2023 - Schöttle - Machine Learning Enabled Image Analysis of Time‐Temperature Sensing Colloidal Arrays.pdf
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Project information

Project title:
Project's official title
Project's id
Elitenetzwerk Bayern
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Open Access Publizieren
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Project financing: Bayerisches Staatsministerium für Wissenschaft, Forschung und Kunst
Deutsche Forschungsgemeinschaft

Further data

Item Type: Article in a journal
Keywords: artificial neural network; film formation; photonic crystals; sensors; smartphone;
structural colors
DDC Subjects: 500 Science > 530 Physics
500 Science > 540 Chemistry
Institutions of the University: Faculties > Faculty of Mathematics, Physics und Computer Science > Department of Physics > Chair Theoretical Physics VII - Computational Materials Design (BayBatt)
Faculties > Faculty of Biology, Chemistry and Earth Sciences > Department of Chemistry > Chair Physical Chemistry I
Research Institutions > Central research institutes > Bayerisches Zentrum für Batterietechnik - BayBatt
Faculties
Faculties > Faculty of Mathematics, Physics und Computer Science
Faculties > Faculty of Mathematics, Physics und Computer Science > Department of Physics
Faculties > Faculty of Biology, Chemistry and Earth Sciences
Faculties > Faculty of Biology, Chemistry and Earth Sciences > Department of Chemistry
Research Institutions
Research Institutions > Central research institutes
Language: English
Originates at UBT: Yes
URN: urn:nbn:de:bvb:703-epub-7588-1
Date Deposited: 19 Mar 2024 07:13
Last Modified: 19 Mar 2024 07:14
URI: https://epub.uni-bayreuth.de/id/eprint/7588

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