Deep Learning Studie zur Hämatoxylin-Eosin histomorphologischen Klassifikation von Urothelkarzinomentitäten mittels Whole-Slide Image Managing Pipeline:
Gespeichert in:
| 1. Verfasser: | |
|---|---|
| Format: | Abschlussarbeit Elektronisch E-Book |
| Sprache: | German |
| Veröffentlicht: |
Erlangen ; Nürnberg
2023
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| Schlagworte: | |
| Online-Zugang: | Volltext Volltext Volltext |
| Beschreibung: | 1 Online-Ressource (41 Seiten) Illustrationen, Diagramme |
| DOI: | 10.25593/open-fau-210 |
Internformat
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Datensatz im Suchindex
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| author | Geyer, Christoph 1988- |
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| format | Thesis Electronic eBook |
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| index_date | 2024-07-03T23:27:49Z |
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| language | German |
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| spelling | Geyer, Christoph 1988- Verfasser (DE-588)1318555280 aut Deep Learning Studie zur Hämatoxylin-Eosin histomorphologischen Klassifikation von Urothelkarzinomentitäten mittels Whole-Slide Image Managing Pipeline vorgelegt von Christoph Geyer Erlangen ; Nürnberg 2023 1 Online-Ressource (41 Seiten) Illustrationen, Diagramme txt rdacontent c rdamedia cr rdacarrier Dissertation Friedrich-Alexander-Universität Erlangen-Nürnberg 2023 Archivierung/Langzeitarchivierung gewährleistet DE-101 pdager 4\p Pipeline (DE-588)4125984-1 gnd 5\p Deep learning (DE-588)1135597375 gnd 6\p Urothelkrebs (DE-588)4187259-9 gnd 7\p Neuronales Netz (DE-588)4226127-2 gnd Deep Learning (DE-588)4113937-9 Hochschulschrift gnd-content https://doi.org/10.25593/open-fau-210 Resolving-System kostenfrei Volltext https://open.fau.de/handle/openfau/30258 Verlag kostenfrei Volltext https://d-nb.info/1314805002/34 Langzeitarchivierung Nationalbibliothek kostenfrei Volltext 1\p emakn 1,00000 20231230 DE-101 https://d-nb.info/provenance/plan#emakn 2\p emasg 0,81511 20231230 DE-101 https://d-nb.info/provenance/plan#emasg 3\p npi 20231229 DE-101 https://d-nb.info/provenance/plan#npi 4\p emagnd 0,14105 20231230 DE-101 https://d-nb.info/provenance/plan#emagnd 5\p emagnd 0,14062 20231230 DE-101 https://d-nb.info/provenance/plan#emagnd 6\p emagnd 0,07357 20231230 DE-101 https://d-nb.info/provenance/plan#emagnd 7\p emagnd 0,07166 20231230 DE-101 https://d-nb.info/provenance/plan#emagnd |
| spellingShingle | Geyer, Christoph 1988- Deep Learning Studie zur Hämatoxylin-Eosin histomorphologischen Klassifikation von Urothelkarzinomentitäten mittels Whole-Slide Image Managing Pipeline 4\p Pipeline (DE-588)4125984-1 gnd 5\p Deep learning (DE-588)1135597375 gnd 6\p Urothelkrebs (DE-588)4187259-9 gnd 7\p Neuronales Netz (DE-588)4226127-2 gnd |
| subject_GND | (DE-588)4125984-1 (DE-588)1135597375 (DE-588)4187259-9 (DE-588)4226127-2 (DE-588)4113937-9 |
| title | Deep Learning Studie zur Hämatoxylin-Eosin histomorphologischen Klassifikation von Urothelkarzinomentitäten mittels Whole-Slide Image Managing Pipeline |
| title_auth | Deep Learning Studie zur Hämatoxylin-Eosin histomorphologischen Klassifikation von Urothelkarzinomentitäten mittels Whole-Slide Image Managing Pipeline |
| title_exact_search | Deep Learning Studie zur Hämatoxylin-Eosin histomorphologischen Klassifikation von Urothelkarzinomentitäten mittels Whole-Slide Image Managing Pipeline |
| title_exact_search_txtP | Deep Learning Studie zur Hämatoxylin-Eosin histomorphologischen Klassifikation von Urothelkarzinomentitäten mittels Whole-Slide Image Managing Pipeline |
| title_full | Deep Learning Studie zur Hämatoxylin-Eosin histomorphologischen Klassifikation von Urothelkarzinomentitäten mittels Whole-Slide Image Managing Pipeline vorgelegt von Christoph Geyer |
| title_fullStr | Deep Learning Studie zur Hämatoxylin-Eosin histomorphologischen Klassifikation von Urothelkarzinomentitäten mittels Whole-Slide Image Managing Pipeline vorgelegt von Christoph Geyer |
| title_full_unstemmed | Deep Learning Studie zur Hämatoxylin-Eosin histomorphologischen Klassifikation von Urothelkarzinomentitäten mittels Whole-Slide Image Managing Pipeline vorgelegt von Christoph Geyer |
| title_short | Deep Learning Studie zur Hämatoxylin-Eosin histomorphologischen Klassifikation von Urothelkarzinomentitäten mittels Whole-Slide Image Managing Pipeline |
| title_sort | deep learning studie zur hamatoxylin eosin histomorphologischen klassifikation von urothelkarzinomentitaten mittels whole slide image managing pipeline |
| topic | 4\p Pipeline (DE-588)4125984-1 gnd 5\p Deep learning (DE-588)1135597375 gnd 6\p Urothelkrebs (DE-588)4187259-9 gnd 7\p Neuronales Netz (DE-588)4226127-2 gnd |
| topic_facet | Pipeline Deep learning Urothelkrebs Neuronales Netz Hochschulschrift |
| url | https://doi.org/10.25593/open-fau-210 https://open.fau.de/handle/openfau/30258 https://d-nb.info/1314805002/34 |
| work_keys_str_mv | AT geyerchristoph deeplearningstudiezurhamatoxylineosinhistomorphologischenklassifikationvonurothelkarzinomentitatenmittelswholeslideimagemanagingpipeline |