activity
20162020
most citedDeepBillboard: Systematic Physical-World Testing of Autonomous Driving Systems

41 citations · 49 across the 3 of their papers we have counts for

collaborators

5 papers

cs.DC2020

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…

cs.SE20197 cited

Characterizing and Detecting CUDA Program Bugs

Mingyuan Wu, Husheng Zhou, Lingming Zhang +2

While CUDA has become a major parallel computing platform and programming model for general-purpose GPU computing, CUDA-induced bug patterns have not yet been well explored. In thi…

cs.CV201841 cited

DeepBillboard: Systematic Physical-World Testing of Autonomous Driving Systems

Husheng Zhou, Wei Li, Yuankun Zhu +4

Deep Neural Networks (DNNs) have been widely applied in many autonomous systems such as autonomous driving. Recently, DNN testing has been intensively studied to automatically gene…

cs.SE2018

DeepRoad: GAN-based Metamorphic Autonomous Driving System Testing

Mengshi Zhang, Yuqun Zhang, Lingming Zhang +2

While Deep Neural Networks (DNNs) have established the fundamentals of DNN-based autonomous driving systems, they may exhibit erroneous behaviors and cause fatal accidents. To reso…

cs.SI20161 cited

Terminal-Set-Enhanced Community Detection in Social Networks

G. Tong, L. Cui, W. Wu +2

Community detection aims to reveal the community structure in a social network, which is one of the fundamental problems. In this paper we investigate the community detection probl…