Open Access
| Issue |
MATEC Web Conf.
Volume 410, 2025
2025 3rd International Conference on Materials Engineering, New Energy and Chemistry (MENEC 2025)
|
|
|---|---|---|
| Article Number | 04014 | |
| Number of page(s) | 8 | |
| Section | Intelligent Systems and Sensor Technologies for Autonomous Operations | |
| DOI | https://doi.org/10.1051/matecconf/202541004014 | |
| Published online | 24 July 2025 | |
- Smith, J., et al. User Needs Analysis for In-Car Navigation Systems. Journal of Intelligent Transportation Systems, 24(3), 123-135 (2020) [Google Scholar]
- Zhang, H., & Li, Y. “Personalized Navigation Model Based on Driving Behavior Data.” Transportation Research Part C: Emerging Technologies,98,45-58 (2019) [Google Scholar]
- Johnson, M., et al. “Real-Time Traffic Prediction Using Deep Learning.” IEEE Transactions on Intelligent Transportation Systems, 22(5), 2345-2357 (2021) [Google Scholar]
- Wang, T., et al. Reinforcement Learning for Route Recommendation in Navigation Systems. Proceedings of the AAAI Conference on ArtificialIntelligence, 32(1), 5678-5686 (2018) [Google Scholar]
- Brown, R., & Davis, K. Design and Evaluation of a Feedback-Based Smart Navigation System.” Human-Computer Interaction, 37(2), 89-102 (2022) [Google Scholar]
- Chen, L., et al. Multimodal Interaction Design for In-Car Navigation Systems. International Journal of Human-Computer Studies, 135, 102-115(2020) [Google Scholar]
- Tang, T., Kuo, W., & Lan, J., et al. Anomaly detection neural network with dualauto-encoders GAN and its industrial inspection applications. Sensors, 20(12), 3336 (2020) [Google Scholar]
- Alberici, D., Camilli, F., Contucci, P., et al. The solution of the deep Boltzmann machine on the Nishimori line. Communications in Mathematical Physics, 387(2) 1191-1214 (2021) [Google Scholar]
- Liu, X., Teng, W., Wu, S., et al. Sparse dictionary learning based adversarial variational auto-encoders for fault identification of wind turbines. Measurement, 183(10), 9810 (2021) [Google Scholar]
- Wang, X., Tang, M., Yang, T., et al. A novel network with multiple attention mechanisms for aspect-level sentiment analysis. Knowledge-Based Systems, 227, 107196 (2021) [Google Scholar]
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.