Cross-domain zero-shot semantic segmentation for unstructured environments via EVA-CLIP model, ensemble prompt engineering, and optimized text-image matching.
Saved in:
| Title: | Cross-domain zero-shot semantic segmentation for unstructured environments via EVA-CLIP model, ensemble prompt engineering, and optimized text-image matching. |
|---|---|
| Authors: | Zhou N; School of Computer Science, Shandong Xiehe University, Shandong, China., Zhao X; Jinan Energy Investment Holding Group Co., Ltd., Shandong, China., Zhou F; School of Computer Science, Shandong Xiehe University, Shandong, China., Li J; School of Computer Science, Shandong Xiehe University, Shandong, China., Yue X; School of Computer Science, Shandong Xiehe University, Shandong, China. |
| Source: | PloS one [PLoS One] 2026 Jun 26; Vol. 21 (6), pp. e0352325. Date of Electronic Publication: 2026 Jun 26 (Print Publication: 2026). |
| Publication Type: | Journal Article |
| Journal Info: | Publisher: Public Library of Science Country of Publication: United States NLM ID: 101285081 Publication Model: eCollection Cited Medium: Internet ISSN: 1932-6203 (Electronic) Linking ISSN: 19326203 NLM ISO Abbreviation: PLoS One Subsets: MEDLINE |
| Database: | MEDLINE Ultimate |
|
Full text is not displayed to guests.
Login for full access.
|
|
| ISSN: | 1932-6203 |
|---|---|
| DOI: | 10.1371/journal.pone.0352325 |
