White matter pathways allow distant parts of the brain to communicate, supporting memory, emotion, and language. One such ...
Official PyTorch implementation of the paper: "Wavelet-Driven Meta-Learning: Unifying Infrared-Visible Fusion and Semantic Segmentation for Robust Scene Perception" (Currently under review / Submitted ...
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 ...
Customized implementation of the U-Net in PyTorch for Kaggle's Carvana Image Masking Challenge from high definition images. This model was trained from scratch with 5k images and scored a Dice ...
The PyTorch team at Meta, stewards of the PyTorch open source machine learning framework, has unveiled Monarch, a distributed programming framework intended to bring the simplicity of PyTorch to ...
Image segmentation is a fundamental process in digital image analysis, with applications in object recognition, medical imaging, and computer vision. Traditional segmentation techniques often struggle ...
Abstract: Medical image segmentation is critical for disease diagnosis and treatment assessment. However, concerns regarding the reliability of segmentation regions persist among clinicians, mainly ...
Abstract: Accurate 3D medical image segmentation is crucial for diagnosis and treatment. Diffusion models demonstrate promising performance in medical image segmentation tasks due to the progressive ...
A research team led by Prof. WANG Huanqin at the Institute of Intelligent Machines, the Hefei Institutes of Physical Science of the Chinese Academy of Sciences, recently proposed a semi-supervised ...
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