时空深度学习Deep Learning for Spatio-Temporal Data张钧波京东智能城市研究院市 京东城市 时空 AI 产品部2020 年7 7 月 22 日2020城市计算夏令营 阅读了该文档的用户还阅读了这些文档 20 p. 无源互调感知波束形成 12 p. 为片上系统布置供电 1 p. 电芯模组及电池组 22 p. 用于管理电信系统中的终端...
O. (2017), "Deep Learning for Spatio- Temporal Modeling: Dynamic Traffic Flows and High Frequency Trading," arXiv preprint arXiv:1705.09851.M. Dixon, N. Polson, and V. Sokolov. Deep learning for spatio-temporal modeling: Dynamic traffic flows and high frequency trading. arXiv preprint arXiv...
Deep Learning for Spatio-Temporal Data Mining: A Survey 2022, IEEE Transactions on Knowledge and Data Engineering T-GCN: A Temporal Graph Convolutional Network for Traffic Prediction 2020, IEEE Transactions on Intelligent Transportation Systems Spatiotemporal multi-graph convolution network for ride-hailing...
Deep-Learning-Based Spatio-Temporal-Spectral Integrated Fusion of Heterogeneous Remote Sensing Image from:TGRS,2022 动机 空间光谱融合(Spatiospectral fusion)和时空融合(Spatiotemporal fusion)仅用于融合来自两个空间、时间和光谱域的信息。→ 时空谱融合 由于多源数据集之间的复杂和非线性关系,目前对集成融合方法的...
Deep-Learning-Based Spatio-Temporal-Spectral Integrated Fusion of Heterogeneous Remote Sensing Images abstract 为了解决STF中的生成heterogeneous images问题: 为此,本文首次提出了一种基于新型深度残差循环生成对抗网络 (GAN) 的异构集成框架。 所提出的网络由前向融合部分和后向退化反馈部分组成。前向部分根据各种观察...
In recent years, numerous neural network models have been put forth, with an emphasis on the applications of raster imagery and spatiotemporal non-imagery datasets. Implementing these models using existing deep learning frame-works, such as PyTorch and TensorFlow, requires nontrivial coding efforts fr...
Julia and Python resources on mathematical epidemiology and epidemiology informed deep learning methods. Most about package information. Main Topics include Data Preprocessing Basic Statistics and Data Visualization Differential Programing and Data Mining such as bayesian inference, deep learning, scientific...
DeepST: A Deep Learning Toolbox for Spatio-Temporal Data Tested on Windows Server 2012 R2. Installation DeepST uses the following dependencies: Keras and its dependencies are required to use DeepST. Please read Keras Configuration for the configuration setting. Theano or TensorFlow, but Theano is...
Spatio-Temporal Super-Resolution Data Assimilation (SRDA) Utilizing Deep Neural Networks with Domain Generalization Technique Toward Four-Dimensional SRDA 基于区域泛化技术的深神经网络时空超分辨率数据同化 Deep learning has recently gained attention in atmospheric and oceanic sciences for its potential to ...
spatio-temporal fields measured on a set of irregular points in space is still under-investigated. To fill this gap, we introduce here a framework for spatio-temporal prediction of climate and environmental data using deep learning. Specifically, we show how spatio-temporal processes can be ...