Quantum federated learning for autonomous vehicle cybersecurity: An analytical review of architectures and threat landscapes. [PDF]
MethodsXT S, Devadas RM.
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Resource-Adaptive Semantic Transmission and Client Scheduling for OFDM-Based V2X Communications. [PDF]
Sensors (Basel)Liu J, Chen Y, Wu W, Tian F.
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Resource Allocation in C-V2X: A review
Cellular Vehicle-to-Everything (C-V2X) is a cutting-edge wireless communication technology that enables seamless connectivity and information exchange among vehicles, infrastructure, networks, and pedestrians.
Tahi, Tahmid Zaman
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Two-Tier Anomaly Detection for V2I Alerting on IoT Vehicle Counts: A Kuwait Corridor Benchmark. [PDF]
Sensors (Basel)AlSaqabi Y.
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Deep Reinforcement Learning for Secure and Low-Latency Communications in UAV-Mounted STAR-RIS Assisted Urban Vehicular Networks. [PDF]
Sensors (Basel)Tang J, Yuan J, Zhao H, Chen M, Peng Y.
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Enhancing V2V Communication by Parsimoniously Leveraging V2N2V Path in Connected Vehicles. [PDF]
Sensors (Basel)Heo S, Song YS, Kang S, Kim H.
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Sensors in Self-Driving Vehicles: A Detailed Literature Review and New Trends. [PDF]
Sensors (Basel)Viktor P, Kiss G.
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State-Aware Resource Allocation for V2X Communications. [PDF]
Sensors (Basel)Sun M, Xu J, Wang J.
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Vehicle Autonomy to Ecosystem Intelligence: A Systematic Review of Dynamic Vision Architectures in Surface Mining Operations. [PDF]
Sensors (Basel)Anti NYD, Frimpong S, Raza MA.
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Deep Learning-Based Channel Estimation Techniques Using IEEE 802.11p Protocol, Limitations of IEEE 802.11p and Future Directions of IEEE 802.11bd: A Review. [PDF]
Sensors (Basel)Bai S, Kilby J, Prasad K.
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