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Found 7 papers, 0 papers with code
LEAF + AIO: Edge-Assisted Energy-Aware Object Detection for Mobile Augmented Reality
In this paper, we design an edge-based energy-aware MAR system that enables MAR devices to dynamically change their configurations, such as CPU frequency, computation model size, and image offloading frequency based on user preferences, camera sampling rates, and available radio resources.
LiveMap: Real-Time Dynamic Map in Automotive Edge Computing
In this paper, we propose LiveMap, a real-time dynamic map, that detects, matches, and tracks objects on the road with crowdsourcing data from connected vehicles in sub-second.
Energy Drain of the Object Detection Processing Pipeline for Mobile Devices: Analysis and Implications
In order to accurately measure the energy consumption on the smartphone and obtain the breakdown of energy consumed by each phase of the object detection processing pipeline, we propose a new measurement strategy.
Architectural Design Alternatives based on Cloud/Edge/Fog Computing for Connected Vehicles
These requirements ask for a well-designed computing architecture to support the Quality-of-Service (QoS) of CV applications.
Networking and Internet Architecture
Runtime-Safety-Guided Policy Repair
The key idea behind our approach is the formulation of a trajectory optimization problem that allows the joint reasoning of policy update and safety constraints.
Are Self-Driving Cars Secure? Evasion Attacks against Deep Neural Networks for Steering Angle Prediction
Deep Neural Networks (DNNs) have tremendous potential in advancing the vision for self-driving cars.
Lookup Table-Based Consensus Algorithm for Real-Time Longitudinal Motion Control of Connected and Automated Vehicles
Different from previous studies in this field where control gains of the consensus algorithm are pre-determined and fixed, we develop algorithms to build up a lookup table, searching for the ideal control gains with respect to different initial conditions of CAVs in real time.
