Maritime image-based weather classification to evaluate the object detection performance
dc.contributor | Aalto-yliopisto | fi |
dc.contributor | Aalto University | en |
dc.contributor.advisor | Chaal, Meriam | |
dc.contributor.author | Pham, Hieu | |
dc.contributor.school | Perustieteiden korkeakoulu | fi |
dc.contributor.supervisor | Käpylä, Maarit | |
dc.date.accessioned | 2023-02-14T09:12:09Z | |
dc.date.available | 2023-02-14T09:12:09Z | |
dc.date.issued | 2022-12-23 | |
dc.format.extent | 20+4 | |
dc.format.mimetype | application/pdf | en |
dc.identifier.uri | https://aaltodoc.aalto.fi/handle/123456789/119738 | |
dc.identifier.urn | URN:NBN:fi:aalto-202302142086 | |
dc.language.iso | en | en |
dc.programme | Aalto Bachelor’s Programme in Science and Technology | fi |
dc.programme.major | Data Science | en |
dc.programme.mcode | SCI3095 | fi |
dc.subject.keyword | supervised machine learning | en |
dc.subject.keyword | computer vision | en |
dc.subject.keyword | image segmentation | en |
dc.subject.keyword | marine object detection | en |
dc.subject.keyword | maritime autonomous surface ship | en |
dc.subject.keyword | unsupervised machine learning | en |
dc.title | Maritime image-based weather classification to evaluate the object detection performance | en |
dc.type | G1 Kandidaatintyö | fi |
dc.type.dcmitype | text | en |
dc.type.ontasot | Bachelor's thesis | en |
dc.type.ontasot | Kandidaatintyö | fi |