Air Pollution Prediction with Multi-Modal Data and Deep Neural Networks

Air Pollution Prediction with Multi-Modal Data and Deep Neural Networks

Air pollution is becoming a rising and serious environmental problem, especially in urban areas affected by an increasing migration rate. The large availability of sensor data enables the adoption of analytical tools to provide decision support capabilities. Employing sensors facilitates air polluti...

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Bibliographic Details
Main Authors:	Jovan Kalajdjieski, Eftim Zdravevski, Roberto Corizzo, Petre Lameski, Slobodan Kalajdziski, Ivan Miguel Pires, Nuno M. Garcia, Vladimir Trajkovik
Format:	Article
Language:	English
Published:	MDPI AG 2020-12-01
Series:	Remote Sensing
Subjects:	air pollution prediction smart city deep learning convolutional neural networks generative adversarial networks
Online Access:	https://www.mdpi.com/2072-4292/12/24/4142

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