Vertebrate paleontology has a numbers problem. Computer vision can help

How many fossils does it take to accurately train an image-based AI algorithm? According to a new study co-authored by Bruce ...
marktechpost

NVIDIA AI releases C-RADIOv4 vision backbone unifying SigLIP2, DINOv3, SAM3 for classification, dense prediction, segmentation workloads at scale

How do you combine SigLIP2, DINOv3, and SAM3 into a single vision backbone without sacrificing dense or segmentation performance? NVIDIA’s C-RADIOv4 is a new agglomerative vision backbone that ...
IEEE

Adaptability of Vision Foundation Models for 3D Medical Image Segmentation

Abstract: Vision Foundation Models (VFMs), such as DINOv2 and SAM, have demonstrated unprecedented generalizability in natural imaging and show strong promise in medical imaging due to their ...
IEEE

SAM-Med3D: A Vision Foundation Model for General-Purpose Segmentation on Volumetric Medical Images

Abstract: Existing volumetric medical image segmentation models are typically task-specific, excelling at specific targets but struggling to generalize across anatomical structures or modalities. This ...