Parameter Efficient Fine-Tuning of CNN-based Foundation Models for Segmenting Organs in 3D CT Images
| dc.rights.license | CC-BY-NC-ND | |
| dc.contributor | Suraj Pai | |
| dc.contributor.advisor | Kaya, Heysem | |
| dc.contributor.author | Hudepohl, Mees | |
| dc.date.accessioned | 2025-11-01T00:01:37Z | |
| dc.date.available | 2025-11-01T00:01:37Z | |
| dc.date.issued | 2025 | |
| dc.identifier.uri | https://studenttheses.uu.nl/handle/20.500.12932/50638 | |
| dc.description.sponsorship | Utrecht University | |
| dc.language.iso | EN | |
| dc.subject | Fine-tuning of CNN-based foundation models using parameter efficient methods for segmenting organs in 3D CT images | |
| dc.title | Parameter Efficient Fine-Tuning of CNN-based Foundation Models for Segmenting Organs in 3D CT Images | |
| dc.type.content | Master Thesis | |
| dc.rights.accessrights | Open Access | |
| dc.subject.courseuu | Artificial Intelligence | |
| dc.thesis.id | 40735 |
