Towards Synthetic Augmentation of Training Datasets Generated by Mobility-on-Demand Service Using Deep Variational Autoencoders

Author:

Gregurić Martin,Vrbanić Filip,Ivanjko Edouard

Publisher

Elsevier BV

Reference25 articles.

1. The concept and impact analysis of a flexible mobility on demand system;Bilge Atasoy;Transportation Research Part C: Emerging Technologies,2015

2. This Dataset Does Not Exist: Training Models from Generated Images;Victor Besnier;ICASSP 2020 -2020 IEEE International Conference on Acoustics, Speech and Signal Processing,2020

3. A variational autoencoder solution for road traffic forecasting systems: Missing data dimension reduction, model selection and anomaly detection;Guillem Boquet;Transportation Research Part C: Emerging Technologies,2020

4. Machine Learning-based traffic prediction models for Intelligent Transportation Systems;Azzedine Boukerche;Computer Networks,2020

5. Traffic Request Generation through a Variational Auto Encoder Approach;Stefano Chiesa;Computers,2022

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