Transfer Learning: Video Prediction and Spatiotemporal Urban Traffic Forecasting

Transfer Learning: Video Prediction and Spatiotemporal Urban Traffic Forecasting

Transfer learning is a modern concept that focuses on the application of ideas, models, and algorithms, developed in one applied area, for solving a similar problem in another area. In this paper, we identify links between methodologies in two fields: video prediction and spatiotemporal traffic fore...

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Bibliographic Details
Main Author: Dmitry Pavlyuk
Format: Article
Language:English
Published: MDPI AG 2020-02-01
Series:Algorithms
Subjects:
urban traffic flows
spatiotemporal models
data-driven
graph convolutional neural networks
spatial filtering
network-wide forecasts
Online Access:https://www.mdpi.com/1999-4893/13/2/39

Internet

https://www.mdpi.com/1999-4893/13/2/39

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