Medical image segmentation is a fundamental component of many clinical applications such as computer-aided diagnosis, radiotherapy planning, and preoperative planning. Its accuracy and stability ...

AI tools like Google’s Veo 3 and Runway can now create strikingly realistic video. WSJ’s Joanna Stern and Jarrard Cole put them to the test in a film made almost entirely with AI. Watch the film and ...

OpenAI is rolling out a new version of ChatGPT Images that promises better instruction-following, more precise editing, and up to 4x faster image generation speeds. The new model, dubbed GPT Image 1.5 ...

A new campaign dubbed 'GhostPoster' is hiding JavaScript code in the image logo of malicious Firefox extensions with more than 50,000 downloads, to monitor browser activity and plant a backdoor. The ...

This repository provides code and workflows to test several state-of-the-art vehicle detection deep learning algorithms —including YOLOX, SalsaNext, RandLA-Net, and VoxelRCNN— on a Flash Lidar dataset ...

Abstract: In this paper, we present UISE, a unified image segmentation framework that achieves efficient performance across various segmentation tasks, eliminating the need for multiple specialized ...

Meta Platforms Inc. today is expanding its suite of open-source Segment Anything computer vision models with the release of SAM 3 and SAM 3D, introducing enhanced object recognition and ...

A new artificial intelligence (AI) tool could make it much easier-and cheaper-for doctors and researchers to train medical imaging software, even when only a small number of patient scans are ...

What if you could replicate the design of any website or transform intricate Figma files into functional code with just a few clicks? It might sound like a developer’s pipe dream, but thanks to ...

Introduction: Laryngeal high-speed video (HSV) is a widely used technique for diagnosing laryngeal diseases. Among various analytical approaches, segmentation of glottis regions has proven effective ...

Abstract: Medical image processing is now the most demanding and expanding field. It is widely used for brain tumor detection and segmentation at healthcare settings and research labs. In this ...

ABSTRACT: We explore the performance of various artificial neural network architectures, including a multilayer perceptron (MLP), Kolmogorov-Arnold network (KAN), LSTM-GRU hybrid recursive neural ...