All systems operational
For Researchers For Publishers Login Register
Home Publications Journal of King Saud University - Computer and Inf
Q1 2026

SAM-FGF: SAM fine grained fine-tuning for ophthalmic image segmentation

Yuancong Liang · Weihua Yang · Junan Huo · Yueqin Diao · Shiqi Zhou · Yanwu Xu · Huihui Fang · Wei Chi
10.1007/s44443-026-00633-6 404 Views 0 Citations
0
Citations
404
Views
Abstract not available for this publication.
Cite this Article (APA)
Yuancong, L., Weihua, Y., Junan, H., Yueqin, D., Shiqi, Z., Yanwu, X., Huihui, F., Wei, C. (2026). SAM-FGF: SAM fine grained fine-tuning for ophthalmic image segmentation. Journal of King Saud University - Computer and Information Sciences. https://doi.org/10.1007/s44443-026-00633-6
Related Papers
A lightweight model for indoor object detection in unstructured scenes based on joint attention and …
Zhizhong Xing; Leping Li; Ying Yang; Wei Zhou; Guolan Ma; Shaochun Chen; Lechun · 2026
13
cites
424
DDM-YOLO: A lightweight oriented detection model for mature daylily fruits in complex environments
Minqiu Kuang; Xuejie Zou; Fangping Xie; Xiaojian Li; Shang Chen; Dawei Liu; Yuxu · 2026
8
cites
430
Information guided Levy flight for robot search in unknown environments
Weitao Zhao; Zati Hakim Azizul; Xin Lyu; Weijie Kuang · 2026
4
cites
411
3
cites
504
Bridging the gap: A comprehensive survey on AI-driven digital twin networks for future wireless syst…
Yousef Sanjalawe; Salam Fraihat; Salam Al-E’mari; Sharif Naser Makhadmeh · 2026
3
cites
417
Access
View Full Text via DOI
Published in
ISSN 1319-1578
Quartile Q1
AMS Score 100
Field Computer Science & AI
Publisher Elsevier / King Saud University
Country 🇸🇦 Saudi Arabia
View Journal Profile →
Authors
Publication Details
Year 2026
Language English
Added 06 Jul 2026