Image processing with MATLAB is a three-step process in which you load, manipulate and then display results as output. While this may sound simple enough, many of the images you work with require ...

We propose Seg-Wild, a novel interactive 3D segmentation framework tailored for unconstrained photo collections. Built on 3D Gaussian Splatting, Seg-Wild embeds multi-dimensional features into 3D ...

A practical implementation of classic image segmentation algorithms in Python using OpenCV and NumPy. This repository provides clear, commented code for Otsu's thresholding and a custom iterative ...

Abstract: Acquiring high-quality annotated data for medical image segmentation is tedious and costly. Semi-supervised segmentation techniques alleviate this burden by leveraging unlabeled data to ...

Abstract: Deep learning models for medical image segmentation often struggle with task-specific characteristics, limiting their generalization to unseen tasks with new anatomies, labels, or modalities ...

On Wednesday, Meta announced an AI model called the Segment Anything Model (SAM) that can identify individual objects in images and videos, even those not encountered during training, reports Reuters.