10 citations · 11 across the 2 of their papers we have counts for
2 papers
eess.IV2023★ 1 cited
SAMIHS: Adaptation of Segment Anything Model for Intracranial Hemorrhage Segmentation
Yinuo Wang, Kai Chen, Weimin Yuan +2
Segment Anything Model (SAM), a vision foundation model trained on large-scale annotations, has recently continued raising awareness within medical image segmentation. Despite the…
cs.CV2023★ 10 cited
Learning to "Segment Anything" in Thermal Infrared Images through Knowledge Distillation with a Large Scale Dataset SATIR
Junzhang Chen, Xiangzhi Bai
The Segment Anything Model (SAM) is a promptable segmentation model recently introduced by Meta AI that has demonstrated its prowess across various fields beyond just image segment…