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Exploiting spatiotemporal patterns for accurate air quality forecasting using deep learning.
Yijun Lin
Nikhit Mago
Yu Gao
Yaguang Li
Yao-Yi Chiang
Cyrus Shahabi
José Luis Ambite
Published in:
SIGSPATIAL/GIS (2018)
Keyphrases
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deep learning
air quality
spatiotemporal patterns
air pollution
unsupervised learning
machine learning
unsupervised feature learning
data mining
mental models
environmental monitoring
computer vision
urban areas
unique features
data sets
shortest path
weakly supervised