We tend to break things down into smaller components to make remembering easier. Event Segmentation Theory explains how we do ...

Meta announced SAM Audio, a new AI model that isolates any specific sound from complex audio or video mixtures, extending the ...

A study has found that the way medical images are prepared before analysis can have a significant impact on the performance ...

Microscopy plays a pivotal role in modern biomedical research, enabling the visualization of fine structures in complex ...

FLAMeS, a new convolutional neural network, enhances MS lesion segmentation accuracy using only T2-weighted FLAIR images, ...

A research team has developed a binocular multispectral stereo imaging (BMSI) system capable of capturing synchronized three-dimensional (3D) plant morphology and multispectral reflectance information ...

Memory is better for event boundaries than for information throughout an event. For example, people might be more likely to ...

Dragonfly 3D World 2025, a major software upgrade that redefines how scientists and engineers explore, analyze, and quantify ...

Abstract: Semi-supervised learning methods based on the mean teacher model have achieved great success in the field of 3-D medical image segmentation. However, most of the existing methods provide ...

Abstract: Ultrasound (US) is generally preferred because it is of low-cost, safe, and non-invasive. US image segmentation is crucial in image analysis. Recently, deep learning-based methods are ...

This repository contains the code implementation for the paper RSRefSeg: Referring Remote Sensing Image Segmentation with Foundation Models, developed based on the MMSegmentation project. The current ...