4 citations · 9 across the 7 of their papers we have counts for
7 papers
Collaborative Multi-BS Power Management for Dense Radio Access Network using Deep Reinforcement Learning
Yuchao Chang, Wen Chen, Jun Li +4
Network energy efficiency is a main pillar in the design and operation of wireless communication systems. In this paper, we investigate a dense radio access network (dense-RAN) cap…
Towards Efficient Architecture and Algorithms for Sensor Fusion
Zhendong Wang, Xiaoming Zeng, Shuaiwen Leon Song +1
The safety of an automated vehicle hinges crucially upon the accuracy of perception and decision-making latency. Under these stringent requirements, future automated cars are usual…
Demystifying Arch-hints for Model Extraction: An Attack in Unified Memory System
Zhendong Wang, Xiaoming Zeng, Xulong Tang +3
The deep neural network (DNN) models are deemed confidential due to their unique value in expensive training efforts, privacy-sensitive training data, and proprietary network chara…
Brief Industry Paper: The Necessity of Adaptive Data Fusion in Infrastructure-Augmented Autonomous Driving System
Shaoshan Liu, Jianda Wang, Zhendong Wang +7
This paper is the first to provide a thorough system design overview along with the fusion methods selection criteria of a real-world cooperative autonomous driving system, named I…
Towards a High-performance and Secure Memory System and Architecture for Emerging Applications
Zhendong Wang, Yang Hu
In this dissertation, we propose a memory and computing coordinated methodology to thoroughly exploit the characteristics and capabilities of the GPU-based heterogeneous system to…
Enabling Efficient Deep Convolutional Neural Network-based Sensor Fusion for Autonomous Driving
Xiaoming Zeng, Zhendong Wang, Yang Hu
Autonomous driving demands accurate perception and safe decision-making. To achieve this, automated vehicles are now equipped with multiple sensors (e.g., camera, Lidar, etc.), ena…
Co-Optimizing Performance and Memory FootprintVia Integrated CPU/GPU Memory Management, anImplementation on Autonomous Driving Platform
Soroush Bateni, Zhendong Wang, Yuankun Zhu +2
Cutting-edge embedded system applications, such as self-driving cars and unmanned drone software, are reliant on integrated CPU/GPU platforms for their DNNs-driven workload, such a…