Abstract: Applications like disaster management, urban planning, and environmental monitoring rely on satellite image categorization. This project develops a machine learning pipeline using ...
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 ...
Abstract: Simultaneous localization and mapping (SLAM) enables robots to localize in uncertain environments and has been widely used in the field of robotics. However, traditional vision SLAM systems ...
Abstract: Data annotation in medical image segmentation is time-consuming and expensive. Semi-supervised learning (SSL) presents a viable solution. However, unlike organ segmentation, current ...