A survey of deep learning applications to autonomous vehicle control
Designing a controller for autonomous vehicles capable of providing adequate performance
in all driving scenarios is challenging due to the highly complex environment and inability to …
in all driving scenarios is challenging due to the highly complex environment and inability to …
A systematic review of perception system and simulators for autonomous vehicles research
F Rosique, PJ Navarro, C Fernández, A Padilla - Sensors, 2019 - mdpi.com
This paper presents a systematic review of the perception systems and simulators for
autonomous vehicles (AV). This work has been divided into three parts. In the first part …
autonomous vehicles (AV). This work has been divided into three parts. In the first part …
A survey of deep learning techniques for autonomous driving
The last decade witnessed increasingly rapid progress in self‐driving vehicle technology,
mainly backed up by advances in the area of deep learning and artificial intelligence (AI) …
mainly backed up by advances in the area of deep learning and artificial intelligence (AI) …
Software engineering for AI-based systems: a survey
AI-based systems are software systems with functionalities enabled by at least one AI
component (eg, for image-, speech-recognition, and autonomous driving). AI-based systems …
component (eg, for image-, speech-recognition, and autonomous driving). AI-based systems …
Software engineering for machine learning: A case study
Recent advances in machine learning have stimulated widespread interest within the
Information Technology sector on integrating AI capabilities into software and services. This …
Information Technology sector on integrating AI capabilities into software and services. This …
Deep learning for self-driving cars: Chances and challenges
Q Rao, J Frtunikj - Proceedings of the 1st international workshop on …, 2018 - dl.acm.org
Artificial Intelligence (AI) is revolutionizing the modern society. In the automotive industry,
researchers and developers are actively pushing deep learning based approaches for …
researchers and developers are actively pushing deep learning based approaches for …
Safely entering the deep: A review of verification and validation for machine learning and a challenge elicitation in the automotive industry
Deep Neural Networks (DNN) will emerge as a cornerstone in automotive software
engineering. However, developing systems with DNNs introduces novel challenges for …
engineering. However, developing systems with DNNs introduces novel challenges for …
A multimodality fusion deep neural network and safety test strategy for intelligent vehicles
Multimodality fusion based on deep neural networks (DNN) is a significant method for
intelligent vehicles. The special characteristics of DNN lead to the issue of AI safety and …
intelligent vehicles. The special characteristics of DNN lead to the issue of AI safety and …
FT-CNN: Algorithm-based fault tolerance for convolutional neural networks
Convolutional neural networks (CNNs) are becoming more and more important for solving
challenging and critical problems in many fields. CNN inference applications have been …
challenging and critical problems in many fields. CNN inference applications have been …
Towards accountable ai: Hybrid human-machine analyses for characterizing system failure
As machine learning systems move from computer-science laboratories into the open world,
their accountability becomes a high priority problem. Accountability requires deep …
their accountability becomes a high priority problem. Accountability requires deep …