Survey of state-of-art autonomous driving technologies with deep learning
Y Huang, Y Chen - 2020 IEEE 20th international conference on …, 2020 - ieeexplore.ieee.org
This is a survey of autonomous driving technologies with deep learning methods. We
investigate the major fields of self-driving systems, such as perception, mapping and …
investigate the major fields of self-driving systems, such as perception, mapping and …
Distribution-aware testing of neural networks using generative models
The reliability of software that has a Deep Neural Network (DNN) as a component is urgently
important today given the increasing number of critical applications being deployed with …
important today given the increasing number of critical applications being deployed with …
An end-to-end curriculum learning approach for autonomous driving scenarios
In this work, we combine Curriculum Learning with Deep Reinforcement Learning to learn
without any prior domain knowledge, an end-to-end competitive driving policy for the …
without any prior domain knowledge, an end-to-end competitive driving policy for the …
Social Interaction‐Aware Dynamical Models and Decision‐Making for Autonomous Vehicles
Interaction‐aware autonomous driving (IAAD) is a rapidly growing field of research that
focuses on the development of autonomous vehicles (AVs) that are capable of interacting …
focuses on the development of autonomous vehicles (AVs) that are capable of interacting …
Too afraid to drive: systematic discovery of semantic dos vulnerability in autonomous driving planning under physical-world attacks
In high-level Autonomous Driving (AD) systems, behavioral planning is in charge of making
high-level driving decisions such as cruising and stopping, and thus highly securitycritical. In …
high-level driving decisions such as cruising and stopping, and thus highly securitycritical. In …
[HTML][HTML] Perception modelling by invariant representation of deep learning for automated structural diagnostic in aircraft maintenance: A study case using DeepSHM
V Ewald, RS Venkat, A Asokkumar… - … Systems and Signal …, 2022 - Elsevier
Predictive maintenance, as one of the core components of Industry 4.0, takes a proactive
approach to maintain machines and systems in good order to keep downtime to a minimum …
approach to maintain machines and systems in good order to keep downtime to a minimum …
Simulation-based test case generation for unmanned aerial vehicles in the neighborhood of real flights
Unmanned aerial vehicles (UAVs), also known as drones, are acquiring increasing
autonomy. With their commercial adoption, the problem of testing their functional and non …
autonomy. With their commercial adoption, the problem of testing their functional and non …
[HTML][HTML] Clinical implementation of deep learning in thoracic radiology: potential applications and challenges
Chest X-ray radiography and computed tomography, the two mainstay modalities in thoracic
radiology, are under active investigation with deep learning technology, which has shown …
radiology, are under active investigation with deep learning technology, which has shown …
Factors affecting autonomous vehicles adoption: a systematic review, proposed framework, and future roadmap
S Al Mansoori, M Al-Emran… - International Journal of …, 2023 - Taylor & Francis
Autonomous vehicles (AVs) offer several benefits, such as improving road safety, mitigating
traffic congestion, and reducing fuel consumption and gas emissions. Despite these …
traffic congestion, and reducing fuel consumption and gas emissions. Despite these …
Reverse and boundary attention network for road segmentation
JY Sun, SW Kim, SW Lee, YW Kim… - Proceedings of the …, 2019 - openaccess.thecvf.com
Road segmentation is an essential task to perceive the driving environment in autonomous
driving and advanced driver assistance systems. With the development of deep learning …
driving and advanced driver assistance systems. With the development of deep learning …