MAGMA: Mobility Analytics Generated from Metrics on ADAS
Author:
Publisher
Springer International Publishing
Link
https://link.springer.com/content/pdf/10.1007/978-3-031-06780-8_12
Reference19 articles.
1. Takács Á, Drexler DA, Galambos P, Rudas IJ, Haidegger T (2018) Assessment and standardization of autonomous vehicles. In: 2018 IEEE 22nd international conference on intelligent engineering systems (INES). IEEE, pp 000185–000192
2. McQueen B (2017) Big data analytics for connected vehicles and smart cities. Artech House
3. Gao H, Cheng B, Wang J, Li K, Zhao J, Li D (2018) Object classification using CNN-based fusion of vision and LIDAR in autonomous vehicle environment. IEEE Trans Industr Inf 14(9):4224–4231
4. Ye D, Yu R, Pan M, Han Z (2020) Federated learning in vehicular edge computing: a selective model aggregation approach. IEEE Access 8:23920–23935
5. Vishnukumar HJ, Butting B, Müller C, Sax E (2017) Machine learning and deep neural network—artificial intelligence core for lab and real-world test and validation for ADAS and autonomous vehicles: AI for efficient and quality test and validation. In: 2017 Intelligent systems conference (IntelliSys). IEEE, pp 714–721
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