Enhanced Air Quality Inference via Multi-View Learning With Mobile Sensing Memory

Author:

Liu Ning1ORCID,Liu Xinyu2,Lin Po-Ting1,Wang Yue1,Zhang Lin2ORCID

Affiliation:

1. Department of Electronic Engineering, Tsinghua University, Beijing, China

2. Tsinghua Shenzhen International Graduate School, Tsinghua University, Shenzhen, China

Funder

Shenzhen Science and Technology Program

Tsinghua-Toyota Joint Research Institute Cross-discipline Program

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

General Engineering,General Materials Science,General Computer Science,Electrical and Electronic Engineering

Reference46 articles.

1. Convolutional lstm network: A machine learning approach for precipitation nowcasting;xingjian;Proc Adv Neural Inf Process Syst,2015

2. Comparison of spatial interpolation methods for the estimation of air quality data

3. Real-Time Single Image and Video Super-Resolution Using an Efficient Sub-Pixel Convolutional Neural Network

4. Encoder-Decoder Residual Network for Real Super-Resolution

5. Image restoration using very deep convolutional encoder-decoder networks with symmetric skip connections;mao;Advances in neural information processing systems,2016

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