Application of deep learning approach for identification and classification of scale defects during hot forming process
| dc.contributor.author | Furman, Szymon | |
| dc.contributor.department | Wydział Inżynierii Metali i Informatyki Przemysłowej | |
| dc.contributor.reviewer | Kusiak, Jan | |
| dc.contributor.supervisor | Rauch, Łukasz | |
| dc.date.available | 2019-11-04T14:31:26Z | |
| dc.date.defence | 2019-09-19 | |
| dc.description.type | praca magisterska | |
| dc.identifier.uri | https://repo.agh.edu.pl/handle/AGH/77733 | |
| dc.language.iso | pol | |
| dc.rights | Access rights reserved | |
| dc.rights.access | zastrzeżony dostęp | |
| dc.rights.accessNote | Praca zawiera informacje chronione lub jest przedmiotem procedury patentowej. | |
| dc.rights.uri | https://repo.agh.edu.pl/info/restricted-access | |
| dc.subject | deep learning | en |
| dc.subject | classification | en |
| dc.subject | scale defects | en |
| dc.subject | hot forming process | en |
| dc.title | Application of deep learning approach for identification and classification of scale defects during hot forming process | pl |
| dc.title.alternative | Application of deep learning approach for identification and classification of scale defects during hot forming process | en |
| dc.type | praca dyplomowa | |
| dspace.entity.type | Publication | |
| thesis.degree.discipline | Informatyka Stosowana (WIMiIP) | pl |
| thesis.degree.formOfStudy | stacjonarne | pl |
| thesis.degree.grantor | Akademia Górniczo-Hutnicza im. Stanisława Staszica w Krakowie | pl |
| thesis.degree.level | studia drugiego stopnia | pl |
| thesis.degree.name | magister inżynier | pl |
| thesis.identifier.dxp | 242154 | |
| thesis.statusORPD | ORPPD1_sent |