Turn photos into 3D with Meta's SAM 3D, using SAM 2 masks and Gaussian splatting, so you can build assets quickly for ...

This repository contains the official implementation of "MedVisionLlama: Leveraging Pre-Trained Large Language Model Layers to Enhance Medical Image Segmentation" by Gurucharan Marthi Krishna Kumar, ...

The global computer vision in healthcare market is projected to expand at a compound annual growth rate (CAGR) of approximately 25% over the forecast period. This robust growth is driven by the ...

Abby Stylianou built an app that asks its users to upload photos of hotel rooms they stay in when they travel. It may seem like a simple act, but the resulting database of hotel room images helps ...

Computer vision libraries have changed how AI models classify images. These tools help digital systems understand visual data very well. They allow AI models to spot complex patterns and objects in ...

Computer vision continues to be one of the most dynamic and impactful fields in artificial intelligence. Thanks to breakthroughs in deep learning, architecture design and data efficiency, machines are ...

Purpose: Brain tumor segmentation with MRI is a challenging task, traditionally relying on manual delineation of regions-of-interest across multiple imaging sequences. However, this data-intensive ...

tumor cases and BI-RADS annotations in categories 2, 3, 4, and 5. In addition, the dataset also contains ground truth delineations that divide the BUS images into tumoral and normal regions. If you ...