Deep-learning-based intelligent neonatal seizure identification using spatial and spectral GNN optimized with the Aquila algorithmdoi:10.3934/math.2024958Nelson, MadhusundarRajendran, SurendranKhalaf, Osamah IbrahimHamam, HabibAIMS Mathematics
Self-attention VS RNN: Self-attention一般都比RNN好。 (有一篇文章专门讨论) Self-attention for Graph: Self-attention是一种GNN。 各种变形,self attention计算量很大,可以减小::《Long Range Arena: A Benchmark for Efficient Transformers》《Efficient Transfomers: A Survey》 GAN 李宏毅 参考李宏毅和【傻瓜式...
The graph-based framework of our ST-GNN model facilitates the integration of spatial interconnectivity and temporal dynamics, capturing the complex interactions within the groundwater system. Our modified Multivariate Time Graph Neural Network model shows significant improvements over traditional methods, ...
Chen L, Shao W, Lv M et al (2022) Aargnn: An attentive attributed recurrent graph neural network for traffic flow prediction considering multiple dynamic factors. IEEE Trans Intell Transp Syst 23(10):17201–17211 Article Google Scholar Yu B, Yin H, Zhu Z (2018) Spatio-temporal graph ...
To solve this issue, this research provides a novel technique for final online goods quality prediction based on deep spatial–temporal graph neural networks (GNN). Our approach can capture hidden spatial information relationships and manage long-time sequences in the processing data by using a ...
此外, 基于GNN的度量方法只关注样本实例层次的信息, 忽略了样本间的分布关系, 导致分类效果不理想. 针对上述问题, 本文提出一种东巴画小样本分类方法(Dongba painting few-shot classification combining spatial information and distribution relationship, DBGN). (1) 针对东巴画背景丰富、纹理复杂的特点, 提出一种...
G. From pattern to process: understanding stream phytobenthic assemblages and implications for determining ecological status. Nova Hedwigia, Beiheft 130, 357–372 (2006). 35. Falkowski, P. G. & LaRoche, J. Acclimation to spectral irradiance in algae. J. Phycol. 27(1), 8–14 (1991). 36...
深度学习:包括CNN、RNN、GNN、GAN等在地理空间智能中的应用 空间优化与规划:主要算法包括遗传算法、蚁群算法、粒子群算法等智能算法 大数据高性能处理:地理空间大数据涵盖了广阔的地理空间范围和丰富的信息内容,数据量通常非常庞大,且来源多样,地理空间大数据是空间数据智能大模型空间智能计算的重要目标。
Satellite hyperspectral imagery is an important data source for large-scale refined land cover classification and mapping, but the high spatial heterogeneity and spectral variability at low spatial resolution and the high computation cost for massive data remain challenges in the research community. In ...
A Spectral–Spatial Transformer Fusion Method for Hyperspectral Video Tracking by Ye Wang, Yuheng Liu, Mingyang Ma and Shaohui Mei * School of Electronics and Information, Northwestern Polytechnical University, Xi’an 710129, China * Author to whom correspondence should be addressed. Remote Sens...