Analyzing style transfer algorithms for segmented images / by Seyed Hadi Seyed.
| Author/creator | Seyed, Seyed Hadi author. |
| Other author | Hart, David Marvin, degree supervisor. |
| Other author | East Carolina University. Department of Computer Science. |
| Format | Theses and dissertations |
| Publication | [Greenville, N.C.] : [East Carolina University], 2024. |
| Description | 1 online resource (45 pages) : color illustrations |
| Supplemental Content | Access via ScholarShip |
| Subjects |
| Summary | The recently developed Segment Anything Model has made grabbing semantically meaningful regions of an image easier than before. This will allow for new applications that build on this approach that weren't previously possible. This thesis investigates integrating the Segment Anything Model with style transfer. Specifically, it proposes Partial Convolution as a way to improve style transfer for segmented regions. Additionally, it investigates how different style transfer techniques are affected by different mask sizes, image statistics, etc. |
| General note | Presented to the Faculty of the Department of Computer Science |
| General note | Advisor: David Hart |
| General note | Title from PDF t.p. (viewed March 5, 2026). |
| Dissertation note | M.S. East Carolina University 2024. |
| Bibliography note | Includes bibliographical references. |
| Technical details | System requirements: Adobe Reader. |
| Technical details | Mode of access: World Wide Web. |
Availability
| Library | Location | Call Number | Status | Item Actions |
|---|---|---|---|---|
| Electronic Resources | Access Content Online | ✔ Available |