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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Project information

Project title:	Project's official title Project's id Computergestütztes Design von (metall-)organischen Halbleitermaterialien und Photo-Elektrokatalysatoren 443721792 Open Access Publizieren No information
Project financing:	Deutsche Forschungsgemeinschaft Elitenetzwerk Bayern

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 - Kolloidale Strukturen und Energiematerialien 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:	03 Sep 2025 07:09
URI:	https://epub.uni-bayreuth.de/id/eprint/7588

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