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

Fuente: arXiv

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Bibliographic Details
Main Authors:	Kulkarni, Pranav, Kanhere, Adway, Savani, Dharmam, Chan, Andrew, Chatterjee, Devina, Yi, Paul H., Parekh, Vishwa S.
Format:	Preprint
Published:	2024
Subjects:	Computer Vision and Pattern Recognition Artificial Intelligence Machine Learning
Online Access:	Acceder al recurso
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Internet

https://arxiv.org/abs/2403.15218