Locating and classifying different types of vehicles is a vital element in numerous
applications of automation and intelligent systems ranging from traffic surveillance to vehicle …

This paper addresses the problem of car detection from aerial images using Convolutional
Neural Networks (CNNs). This problem presents additional challenges as compared to car …

An apparatus and method for lane feature detection from an image is performed according
to predetermined path geometry. An image including at least one path is received. The …

Parametric models that represent layout in terms of scene attributes are an attractive avenue
for road scene understanding in autonomous navigation. Prior works that rely only on …

Determining roads from satellite images has gained more research interest after the recent
progress on data-heavy machine learning methods which are also accelerated by the …

High-Definition (HD) maps have drawn lots of attention in the field of autonomous driving in
recent years, due to their high localization precision and detailed environmental information …

Für viele Anwendungen im Bereich des automatisierten Fahrens fehlt es bisher an einer
geeigneten, echtzeitfähigen Architektur, die Kartenmerkmale darstellen und damit eine …

This master's thesis aim is to show the application of semantic segmentation in aerial
imagery using different convolutional neural networks (CNNs). Semantically segmenting …

Semantic segmentation is a process of classifying each pixel in the image. Due to its
advantages, semantic segmentation is used in many tasks like cancer detection, robot …