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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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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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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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Deep Learning for Autonomous Driving
2019 Digital Image Computing: Techniques and Applications (DICTA), 2019In this paper we look at Deep Learning methods using TensorFlow for autonomous driving tasks. Using scale model vehicles in a traffic scenario similar to the Audi Autonomous Driving Cup and the Carolo Cup, we successfully used Deep Learning stacks for the two independent tasks of lane keeping and traffic sign recognition.
Nicholas Burleigh +2 more
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Lane Finding for Autonomous Driving
2019The problem of lane finding is one of the main components of scene understanding for autonomous driving. This paper presents the application of computer vision to lane finding on motorways. This technique is used to transform an image captured by a camera into binary form and apply a moving histogram window to derive the most likely position of the ...
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A comparative study of state-of-the-art driving strategies for autonomous vehicles
Accident Analysis and Prevention, 2021Xiangbin Wu, Fei-Yue Wang, Zhiheng Li
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The development of autonomous driving technology: perspectives from patent citation analysis
Transport Reviews, 2021John S Liu, Mei Hsiu-Ching Ho
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A survey of deep learning techniques for autonomous driving
Journal of Field Robotics, 2020Bogdan Trasnea +2 more
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