Abstract: Accurate segmentation of vertebrae in computed tomography (CT) images possess serious challenges due to the irregular vertebral boundaries, low contrast and brightness, and noise in CT scans ...
Abstract: Flood mapping using remote sensing data is critical to disaster response, especially in real-time monitoring and edge deployment. However, existing deep-learning (DL) models often face ...
SAT-UNET is a deep learning model for cloud semantic segmentation, designed for remote sensing imagery. This repository provides all necessary code, configuration files, and utilities to train, ...
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