2023年1月24日 · To overcome this limitation, we propose a semantic-aware graph network (SAGN) for HRRS images. SAGN consists of a dense feature pyramid network (DFPN), an …

To address these deficiencies, this article develops a sharpening-aware graph network (SAGN) for achieving high-quality HSI CD. First, to counteract the weakening of differences caused by …

Paper Name: "SAGN: Semantic-Aware Graph Network for Remote Sensing Scene Classification" Paper Link: https://ieeexplore.ieee.org/abstract/document/10025702 Note: The key code has …

To overcome this limitation, we propose a semantic-aware graph network (SAGN) for HRRS images. SAGN consists of a dense feature pyramid network (DFPN), an adaptive semantic …

A sharpening-aware graph network (SAGN) is developed for achieving high-quality HSI CD and a novel Laplacian sharpening-based graph convolution (LSGC) module is proposed to …

Due to the absence of a gold standard for threshold selection, brain networks constructed with inappropriate thresholds risk topological degradation or contain noise connections. Therefore, …

2024年8月15日 · Experiments demonstrate that brain physiological patterns associated with different emotional states are separable and rooted in weakly coupled brain networks. In …

SAGN是一种结合语义和自适应图网络的骨架动作识别模型，旨在解决现有方法忽视语义特征和计算量大的问题。 通过融合动态特性和骨骼信息，SAGN在训练过程中引入了自适应网络，使注 …

Official implementation of SAGNN for our AAAI 2023 paper: Substructure Aware Graph Neural Networks.

We propose a semantic and adaptive graph network (SAGN) with relatively little computation. Figure~\ref {fig:networks} shows the overall framework.