Revisiting Convolutional Neural Networks for Urban Flow Analytics

Cited by: 2|Bibtex|Views85
Other Links: arxiv.org

Abstract:

Convolutional Neural Networks (CNNs) have been widely adopted in raster-based urban flow analytics by virtue of their capability in capturing nearby spatial context. By revisiting CNN-based methods for different analytics tasks, we expose two common critical drawbacks in the existing uses: 1) inefficiency in learning global context, and...More

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