Contributing person datacite.contributor.ContactPerson	Benjamin Kruppke
Contributing person datacite.contributor.DataCollector	Guofan Lv
Countries to which the data refer datacite.geolocation.iso3166	GERMANY
Description of the data datacite.resourceType	This programm can be used to label microscopic images of cells and to assess their maturation state. The version uploaded is specifially designed to identify monocytes and osteoclasts of various number of cell nuclei.
Type of the data datacite.resourceTypeGeneral	Software
Total size of the dataset datacite.size	2834673809
Author dc.contributor.author	Lv, Guofan
Author dc.contributor.author	Kruppke, Benjamin
Upload date dc.date.accessioned	2025-03-11T10:24:55Z
Publication date dc.date.available	2025-03-11T10:24:55Z
Data of data creation dc.date.created	2024-02-07
Publication date dc.date.issued	2025-03-11
Abstract of the dataset dc.description.abstract	This programm is part of the project, that has successfully trained an AI that can classify and calculate four cell types. This AI is practical and has a bright future in terms of cell identification. YOLOv5m was used for this AI training. With a better computer configuration, YOLOv5x can be used for training to obtain an even better AI model. Ultralytics is the software company that developed YOLOv5. It released the latest YOLO series version, YOLOv8, in January 2023. This new framework can lead to better training results. In addition to known improvement methods, AI technology has greater prospects. YOLOv5 can be combined with other AI frameworks to predict cell growth trends. AI can also make suggestions about cell culture conditions (temperature, media, frequency of media exchange, etc.) based on growth trends. The AI framework can also be combined with other devices, for example, to control robotic arms and microscopes to automatically complete image acquisition. With the help of this AI, laboratory staff can be freed from the tedious task of counting cells and do much more.
Public reference to this page dc.identifier.uri	https://opara.zih.tu-dresden.de/handle/123456789/1247
Public reference to this page dc.identifier.uri	https://doi.org/10.25532/OPARA-730
Publisher dc.publisher	Technische Universität Dresden
Licence dc.rights	Attribution-NonCommercial-NoDerivatives 4.0 International	en
URI of the licence text dc.rights.uri	http://creativecommons.org/licenses/by-nc-nd/4.0/
Specification of the discipline(s) dc.subject.classification	4::43::406::406-02
Title of the dataset dc.title	OC_Identifier - Programm to use OC trained AI for the assessment of their state of maturation

OC_Identifier - Programm to use OC trained AI for the assessment of their state of maturation

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