Results 41 to 50 of about 497,808 (317)

Unraveled Multilevel Transformation Networks for Predicting Sparsely-Observed Spatiotemporal Dynamics [PDF]

, 2022
In this paper, we address the problem of predicting complex, nonlinear spatiotemporal dynamics when available data is recorded at irregularly-spaced sparse spatial locations. Most of the existing deep learning models for modeling spatiotemporal dynamics are either designed for data in a regular grid or struggle to uncover the spatial relations from ...
arxiv   +1 more source

Traffic accident risk prediction based on deep learning and spatiotemporal features of vehicle trajectories. [PDF]

PLoS One
Li H, Chen L.
europepmc   +2 more sources

Spatiotemporal Deep Learning Model for Citywide Air Pollution Interpolation and Prediction [PDF]

2020 IEEE International Conference on Big Data and Smart Computing (BigComp), 2020
Accepted at ...
Van-Duc Le, Sang Kyun Cha, Tien-Cuong Bui   +2 more
openaire   +3 more sources

Deep Learning for Spatiotemporal Nowcasting

, 2021
Nowcasting ? short-term forecasting using current observations ? is a key challenge that human activities have to face on a daily basis. We heavily rely on short-term meteorological predictions in domains such as aviation, agriculture, mobility, and energy production.
openaire   +1 more source

Source Acquisition Device Identification from Recorded Audio Based on Spatiotemporal Representation Learning with Multi-Attention Mechanisms

Entropy, 2023
Source acquisition device identification from recorded audio aims to identify the source recording device by analyzing the intrinsic characteristics of audio, which is a challenging problem in audio forensics.
Chunyan Zeng, Shixiong Feng, Dongliang Zhu, Zhifeng Wang   +3 more
doaj   +1 more source

Enhanced Multi-Stream Remote Sensing Spatiotemporal Fusion Network Based on Transformer and Dilated Convolution

Remote Sensing, 2022
Remote sensing images with high temporal and spatial resolutions play a crucial role in land surface-change monitoring, vegetation monitoring, and natural disaster mapping.
Weisheng Li, Dongwen Cao, Minghao Xiang
doaj   +1 more source

Network SpaceTime AI: Concepts, Methods and Applications [PDF]

Journal of Geodesy and Geoinformation Science, 2022
SpacetimeAI and GeoAI are currently hot topics, applying the latest algorithms in computer science, such as deep learning, to spatiotemporal data. Although deep learning algorithms have been successfully applied to raster data due to their natural ...
Tao CHENG,Yang ZHANG,James HAWORTH
doaj   +1 more source

A Novel Interpretable Deep Learning Model for Ozone Prediction

Applied Sciences, 2023
Due to the limited understanding of the physical and chemical processes involved in ozone formation, as well as the large uncertainties surrounding its precursors, commonly used methods often result in biased predictions.
Xingguo Chen, Yang Li, Xiaoyan Xu, Min Shao   +3 more
doaj   +1 more source

A Hybrid Spatiotemporal Deep Learning Model for Short-Term Metro Passenger Flow Prediction

Journal of Advanced Transportation, 2020
The primary objective of this study is to predict the short-term metro passenger flow using the proposed hybrid spatiotemporal deep learning neural network (HSTDL-net).
Hao Zhang, Jie He, Jie Bao, Qiong Hong, Xiaomeng Shi   +4 more
doaj   +1 more source

A Novel Deep Learning-Based Spatiotemporal Fusion Method for Combining Satellite Images with Different Resolutions Using a Two-Stream Convolutional Neural Network

Remote Sensing, 2020
Spatiotemporal fusion is considered a feasible and cost-effective way to solve the trade-off between the spatial and temporal resolution of satellite sensors.
Duo Jia, Changqing Song, Changxiu Cheng, Shi Shen, Lixin Ning, Chun Hui   +5 more
doaj   +1 more source