This article presents a comprehensive survey of deep learning applications for object
detection and scene perception in autonomous vehicles. Unlike existing review papers, we …

Autonomous, or self-driving, cars are emerging as the solution to several problems primarily
caused by humans on roads, such as accidents and traffic congestion. However, those …

Synthetic data in machine learning for medicine and healthcare | Nature Biomedical Engineering
Skip to main content Thank you for visiting nature.com. You are using a browser version with …

This paper provides a comprehensive survey of techniques for testing machine learning
systems; Machine Learning Testing (ML testing) research. It covers 144 papers on testing …

The advancement of artificial intelligence (AI) has truly stimulated the development and
deployment of autonomous vehicles (AVs) in the transportation industry. Fueled by big data …

The empowering unmanned aerial vehicles (UAVs) have been extensively used in providing
intelligence such as target tracking. In our field experiments, a pretrained convolutional …

Automated Driving Systems (ADS) have made great achievements in recent years thanks to
the efforts from both academia and industry. A typical ADS is composed of multiple modules …

Abstract Context Machine Learning (ML) has been at the heart of many innovations over the
past years. However, including it in so-called “safety-critical” systems such as automotive or …

When deploying machine learning models in real-world applications, an open-world
learning framework is needed to deal with both normal in-distribution inputs and undesired …

Predicting the motion of a driver's vehicle is crucial for advanced driving systems, enabling
detection of potential risks towards shared control between the driver and automation …