Deep convolutional generative adversarial networks for traffic data imputation encoding time series as images

no code implementations • 5 May 2020 • Tongge Huang, Pranamesh Chakraborty, Anuj Sharma

This study shows that the proposed model can significantly improve the traffic data imputation accuracy in terms of Mean Absolute Error (MAE) and Root Mean Squared Error (RMSE) compared to state-of-the-art models on the benchmark dataset.

Decision Making Generative Adversarial Network +6