IEEE

A Multi-Resolution Hybrid CNN-Transformer Network With Scale-Guided Attention for Medical Image Segmentation

Abstract: Medical image segmentation remains a challenging task due to the intricate nature of anatomical structures and the wide range of target sizes. In this paper, we propose a novel U-shaped ...
GitHub

OpenWorldSAM: Extending SAM2 for Universal Image Segmentation with Language Prompts [NeurIPS 2025]

OpenWorldSAM pushes the boundaries of SAM2 by enabling open-vocabulary segmentation with flexible language prompts. [2026-1-4]: Demo release: we’ve added simple demos to run OpenWorldSAM on images ...
GitHub

VeloxSeg: Johnson-Lindenstrauss Lemma Guided Network for Efficient 3D Medical Segmentation

Overview of VeloxSeg. VeloxSeg employs an encoder-decoder architecture with Paired Window Attention (PWA) and Johnson-Lindenstrauss lemma-guided convolution (JLC) on the left, using 1x1 convolution as ...
IEEE

A Recent Survey of Vision Transformers for Medical Image Segmentation

Abstract: Medical image segmentation plays a crucial role in various healthcare applications, enabling accurate diagnosis, treatment planning, and disease monitoring. Convolutional Neural Networks ...
TMCnet

Bridging Silence: A Real-Time Sign Language to English Text Translation System Using Python, OpenCV, and Convolutional Neural Networks

Bridging communication gaps between hearing and hearing-impaired individuals is an important challenge in assistive technology and inclusive education. In an attempt to close that gap, I developed a ...