Deep Convolutional Neural Networks (CNNs) have recently become the subject of rigorous investigation especially due to their favourable properties in the field of computer vision and hence have been utilized in numerous related applications. Among these, image classification and semantic segmentation have acquired particular research interest. This work is a part of an applied project funded by Reach-U - a company specializing in geographic information systems, location based solutions and cartography - and is geared towards smart city applications. In particular, the topic of this thesis is focused on the detection of road features which includes both semantic segmentation and image classification.