Sam Deep Learning
![[2310.08820] Learning to Adapt SAM for Segmenting Cross-domain Point Clouds](https://ar5iv.labs.arxiv.org/html/2310.08820/assets/x1.png "Sam Deep Learning")
![[论文评述] SAM-R1: Leveraging SAM for Reward Feedback in Multimodal ...](https://moonlight-paper-snapshot.s3.ap-northeast-2.amazonaws.com/arxiv/sam-r1-leveraging-sam-for-reward-feedback-in-multimodal-segmentation-via-reinforcement-learning-1.png "Sam Deep Learning")
![[论文评述] SAM-Guided Robust Representation Learning for One-Shot 3D ...](https://moonlight-paper-snapshot.s3.ap-northeast-2.amazonaws.com/arxiv/sam-guided-robust-representation-learning-for-one-shot-3d-medical-image-segmentation-1.png "Sam Deep Learning")
![[論文レビュー] SAM-Fed: SAM-Guided Federated Semi-Supervised Learning for ...](https://moonlight-paper-snapshot.s3.ap-northeast-2.amazonaws.com/arxiv/sam-fed-sam-guided-federated-semi-supervised-learning-for-medical-image-segmentation-1.png "Sam Deep Learning")
![SAM (Successive Approximation Model) for Instructional Design [2022]](https://www.valamis.com/wp-content/uploads/2022/09/SAM-model-full-version.png "Sam Deep Learning")
![[2305.03678] Towards Segment Anything Model (SAM) for Medical Image ...](https://ar5iv.labs.arxiv.org/html/2305.03678/assets/DeSAM.jpg "Sam Deep Learning")
![[论文评述] A Federated Learning-Friendly Approach for Parameter-Efficient ...](https://moonlight-paper-snapshot.s3.ap-northeast-2.amazonaws.com/arxiv/a-federated-learning-friendly-approach-for-parameter-efficient-fine-tuning-of-sam-in-3d-segmentation-1.png "Sam Deep Learning")
![[2306.06211] Segment Anything in Vision Foundation Model Era: A Survey ...](https://ar5iv.labs.arxiv.org/html/2306.06211/assets/fig_survey/SAM_labeling.png "Sam Deep Learning")
![[SAM]A Comprehensive Survey on Segment Anything Model for Vision and ...](https://i-blog.csdnimg.cn/blog_migrate/156ffa2b65582dcfb8ebf3399c1fccc9.png "Sam Deep Learning")
![[SAM]A Comprehensive Survey on Segment Anything Model for Vision and ...](https://img-blog.csdnimg.cn/90a9c3fd678d40938e1b968b80edca84.png "Sam Deep Learning")
![[2305.03678] Towards Segment Anything Model (SAM) for Medical Image ...](https://ar5iv.labs.arxiv.org/html/2305.03678/assets/SAM.jpg "Sam Deep Learning")
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