MAE, a self-supervised learning framework designed to automate 3D segmentation of plant organs from point cloud data.
Abstract: In this paper, we introduce U-Net v2, a new robust and efficient U-Net variant for medical image segmentation. It aims to augment the infusion of semantic information into low-level features ...
Abstract: Deep-learning-based methods have shown superior performance in monocular depth estimation tasks. However, the existing methods often overlook small-scale objects and vertical information ...
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