Results 211 to 220 of about 65,126 (264)
ACNet: An Attention-Convolution Collaborative Semantic Segmentation Network on Sensor-Derived Datasets for Autonomous Driving. [PDF]
Sensors (Basel)Zhang Q, Hua K, Zhang Z, Zhao Y, Chen P.
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Insights of semantic segmentation using the DeepLab architecture for autonomous driving. [PDF]
MethodsXSubhedar J, Bachute MR.
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Design, Implementation and Evaluation of an Immersive Teleoperation Interface for Human-Centered Autonomous Driving. [PDF]
Sensors (Basel)Bouzón I +5 more
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SupportingTrust in Autonomous Driving
Proceedings of the 22nd International Conference on Intelligent User Interfaces, 2017Autonomous cars will likely hit the market soon, but trust into such a technology is one of the big discussion points in the public debate. Drivers who have always been in complete control of their car are expected to willingly hand over control and blindly trust a technology that could kill them.
Renate Häuslschmid +3 more
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Magnetic Resonance in Chemistry, 2016
The automatic analysis of NMR data has been a much‐desired endeavour for the last six decades, as it is the case with any other analytical technique. This need for automation has only grown as advances in hardware; pulse sequences and automation have opened new research areas to NMR and increased the throughput of data.
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The automatic analysis of NMR data has been a much‐desired endeavour for the last six decades, as it is the case with any other analytical technique. This need for automation has only grown as advances in hardware; pulse sequences and automation have opened new research areas to NMR and increased the throughput of data.
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Visual Evaluation for Autonomous Driving
IEEE Transactions on Visualization and Computer Graphics, 2022Autonomous driving technologies often use state-of-the-art artificial intelligence algorithms to understand the relationship between the vehicle and the external environment, to predict the changes of the environment, and then to plan and control the behaviors of the vehicle accordingly.
Yijie Hou +7 more
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Multimedia for Autonomous Driving
IEEE MultiMedia, 2019Multimedia has played an indispensable role in the success of various real-world applications, from smart healthcare to intelligent surveillance systems. In this new era of technology, one of these essential and useful applications is autonomous driving or self-driving cars.
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Consumers’ understanding of autonomous driving
Information Technology & People, 2018PurposeThe purpose of this paper is to explore consumers’ understanding of autonomous driving by comparing perceptions of occasional drivers (ODs) and frequent drivers (FDs).Design/methodology/approachData were gathered through semi-structured interviews with 41 drivers.
Cho, Eunae, Jung, Yoonhyuk
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Addressing the uncertainties in autonomous driving
SIGSPATIAL Special, 2016Autonomous driving is a highly complex sensing and control problem. Today's vehicles may include many different compositions of sensor sets including the newer more sophisticated sensors like radar, cameras, and lidar. Each sensor in the car provides specific information about the environment at varying levels and has an inherent uncertainty and ...
Jane MacFarlane, Matei Stroila
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Intrusion-Tolerant Autonomous Driving
2018 IEEE 21st International Symposium on Real-Time Distributed Computing (ISORC), 2018Fully autonomous driving is one if not the killer application for the upcoming decade of real-time systems. However, in the presence of increasingly sophisticated attacks by highly skilled and well equipped adversarial teams, autonomous driving must not only guarantee timeliness and hence safety.
Marcus Völp +1 more
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