Segment Anything Model (SAM)
PulseAugur coverage of Segment Anything Model (SAM) — every cluster mentioning Segment Anything Model (SAM) across labs, papers, and developer communities, ranked by signal.
2 day(s) with sentiment data
-
New S3AM framework enhances multi-modal salient object detection
Researchers have developed S$^3$AM, a novel single-stream framework for multi-modal salient object detection. This approach integrates a reliability-calibrated frequency adapter with the Segment Anything Model (SAM) bac…
-
New framework enhances medical image segmentation with SAM and active learning
Researchers have developed SUGFW+, a novel framework designed to improve medical image segmentation models, particularly in scenarios with limited annotated data. This approach leverages the Segment Anything Model (SAM)…
-
Meta's SAM fine-tuned for improved waste segmentation accuracy
Researchers have explored the effectiveness of Meta AI's Segment Anything Model (SAM) for waste segmentation tasks. By fine-tuning SAM on three specific waste datasets, they found that the SAM-ViT-H model significantly …
-
New method cuts cell segmentation clicks from thousands to one per type
Researchers have developed a new method called Chain-of-Prompts (CoP) for cell instance segmentation, significantly reducing the annotation effort required. This training-free framework leverages foundation models like …
-
CLIP-Guided SAM enhances segmentation with parameter-efficient semantic conditioning
Researchers have developed CLIP-Guided SAM, a new parameter-efficient framework that enhances the Segment Anything Model (SAM) by incorporating semantic understanding. This method injects CLIP-derived features directly …
-
Deep learning automates virus titration from lab images
Researchers have developed a deep learning system to automate plaque counting and virus titration from laboratory images. The system uses two models derived from the Segment Anything Model (SAM) to segment wells and the…
-
New AI method matches human accuracy in organoid image segmentation
Researchers have developed a new composite method for segmenting organoid images, combining the Segment Anything Model (SAM) with a domain-specific tool. This approach aims to accurately measure the size and shape of de…