With the rapid development of convolutional neural networks in image processing, deep learning has been widely applied to medical image segmentation tasks, including liver, retinal vessels, nuclei, ...

Learn how the Inception Net V1 architecture works and how to implement it from scratch using PyTorch. Perfect for deep learning enthusiasts wanting a hands-on understanding of this classic ...

Net zero refers to the goal of achieving a state of balance between the carbon emitted into the atmosphere and the carbon removed from it. U.S. Energy Secretary Chris Wright's sharp criticism of net ...

Abstract: Combining low-spatial-resolution hyperspectral image (LrHSI) with high-spatial-resolution multispectral image (HrMSI) serves as an effective strategy for enhancing the spatial fidelity of ...

U-Net and its variants have been widely used in the field of image segmentation. In this paper, a lightweight multi-scale Ghost U-Net (MSGU-Net) network architecture is proposed. This can efficiently ...

Accurate brain tumour segmentation is critical for diagnosis and treatment planning, yet challenging due to tumour complexity. Manual segmentation is time-consuming and variable, necessitating ...