Robot localization in RGB-D images using PCA and CNN
| dc.contributor.advisor | Cansever, Galip | |
| dc.contributor.author | Taha, Alwaled Khalid | |
| dc.date.accessioned | 2023-09-08T06:44:09Z | |
| dc.date.available | 2023-09-08T06:44:09Z | |
| dc.date.issued | 2022 | en_US |
| dc.date.submitted | 2022 | |
| dc.department | Enstitüler, Lisansüstü Eğitim Enstitüsü, Bilişim Teknolojileri Ana Bilim Dalı | en_US |
| dc.description.abstract | Human beings have always utilized the resources available to them as tools to assist them in completing activities in the most efficient, timely, and safe manner possible. As technology improves, these instruments are incorporated into more sophisticated machines capable of doing difficult tasks accurately and often better than a person could. In this research, we will demonstrate how to accomplish a robust robot localization by reducing three-dimensional photos to two-dimensional images using the PCA technique and then using CNN to extract and classify the images' features. | en_US |
| dc.identifier.citation | Taha, Alwaled Khalid. (2022). Robot localization in RGB-D images using PCA and CNN. (Yayınlanmamış yüksek lisans tezi). Altınbaş Üniversitesi, Lisansüstü Eğitim Enstitüsü, İstanbul. | en_US |
| dc.identifier.uri | https://hdl.handle.net/20.500.12939/3909 | |
| dc.identifier.yoktezid | 796154 | |
| dc.institutionauthor | Taha, Alwaled Khalid | |
| dc.language.iso | en | |
| dc.publisher | Altınbaş Üniversitesi / Lisansüstü Eğitim Enstitüsü | en_US |
| dc.relation.publicationcategory | Tez | en_US |
| dc.rights | info:eu-repo/semantics/closedAccess | en_US |
| dc.subject | CNN | en_US |
| dc.subject | PCA | en_US |
| dc.subject | RGBD | en_US |
| dc.subject | Localization | en_US |
| dc.title | Robot localization in RGB-D images using PCA and CNN | |
| dc.type | Master Thesis |
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