| dc.contributor.advisor | Bruzzone, Agostino <1965> | |
| dc.contributor.advisor | Cerrone, Carmine <1980> | |
| dc.contributor.author | Etesami, Mohammad <1993> | |
| dc.date.accessioned | 2023-11-02T15:17:28Z | |
| dc.date.available | 2023-11-02T15:17:28Z | |
| dc.date.issued | 2023-10-25 | |
| dc.identifier.uri | https://unire.unige.it/handle/123456789/6793 | |
| dc.description.abstract | The weave pattern (texture) of woven fabric is considered to be an important factor of the design and production of high-quality fabric. Traditionally, the recognition of woven fabric has a lot of challenges due to its manual visual inspection. Moreover, the approaches based on early machine learning algorithms directly depend on handcrafted features, which are time-consuming and error-prone processes. Hence, an automated system is needed for classification of woven fabric to improve productivity. in this article we want to use CNN algoritum to recognition of texture. we use 6 different textures for it | it_IT |
| dc.description.abstract | The weave pattern (texture) of woven fabric is considered to be an important factor of the design and production of high-quality fabric. Traditionally, the recognition of woven fabric has a lot of challenges due to its manual visual inspection. Moreover, the approaches based on early machine learning algorithms directly depend on handcrafted features, which are time-consuming and error-prone processes. Hence, an automated system is needed for classification of woven fabric to improve productivity. in this article we want to use CNN algoritum to recognition of texture. we use 6 different textures for it | en_UK |
| dc.language.iso | en | |
| dc.rights | info:eu-repo/semantics/closedAccess | |
| dc.title | RICONOSCIMENTO DELLA TEXTURE MEDIANTE DEEP LEARNING | it_IT |
| dc.title.alternative | TEXTURE RECOGNITION BY DEEP LEARNING | en_UK |
| dc.type | info:eu-repo/semantics/masterThesis | |
| dc.subject.miur | MAT/09 - RICERCA OPERATIVA | |
| dc.publisher.name | Università degli studi di Genova | |
| dc.date.academicyear | 2022/2023 | |
| dc.description.corsolaurea | 10728 - ENGINEERING TECHNOLOGY FOR STRATEGY (AND SECURITY) | |
| dc.description.area | 9 - INGEGNERIA | |
| dc.description.department | 100026 - DIPARTIMENTO DI INGEGNERIA NAVALE, ELETTRICA, ELETTRONICA E DELLE TELECOMUNICAZIONI | |
