Anytime, Anywhere, Anyone: Investigating the Feasibility of Segment Anything Model for Crowd-Sourcing Medical Image Annotations

22 March 2024

Papers citing "Anytime, Anywhere, Anyone: Investigating the Feasibility of Segment Anything Model for Crowd-Sourcing Medical Image Annotations"

3 / 3 papers shown

Title
There is no SAMantics! Exploring SAM as a Backbone for Visual Understanding Tasks Miguel Espinosa Chenhongyi Yang Linus Ericsson Jingyu Sun Elliot J. Crowley VLM 75 0 0 22 Nov 2024
A Survey on Segment Anything Model (SAM): Vision Foundation Model Meets Prompt Engineering Chaoning Zhang Fachrina Dewi Puspitasari Sheng Zheng Chenghao Li Yu Qiao ... Caiyan Qin François Rameau Lik-Hang Lee Sung-Ho Bae Choong Seon Hong VLM 84 63 0 12 May 2023
U-Net: Convolutional Networks for Biomedical Image Segmentation Olaf Ronneberger Philipp Fischer Thomas Brox SSeg 3DV 336 75,888 0 18 May 2015