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Automatic semantic segmentation of images is becoming a very prominent research field with many promising and reliable solutions already available. Labelled images as input for the photogrammetric pip...
Point cloud segmentation is an important first step in categorising a raw point cloud data. This step is necessary in order to better manage the data and generate other derivative products, e.g. 3D GI...
This paper addresses the task of semantic segmentation of orthoimagery using multimodal data e.g. optical RGB, infrared and digital surface model. We propose a deep convolutional neural network archit...
The current on-going boom in the field of Building Information Modeling (BIM) and 3D GIS is widely being explored for vast urban related applications, analyses and simulations. Large amount of 3D city...
The need to share information about architectural heritage effectively after a disaster event, in order to foster its preservation, requires the use of a common language between the involved actors an...
he last decade has witnessed increasing interest in the study of urban stocks and flows. This paper provides a literature review for different studies of urban stocks and flows. The review shows that ...
Labeling 3D point cloud data with traditional supervised learning methods requires considerable labelled samples, the collection of which is cost and time expensive. This work focuses on adopting doma...
In the field of autonomous driving, semantic information of lanes is very important. This paper proposes a method of automatic detection of lanes and extraction of semantic information from onboard ca...
At present, intelligent video analysis technology has been widely used in various fields. Object tracking is one of the important part of intelligent video surveillance, but the traditional target tra...
Detecting unregistered buildings from aerial images is an important task for urban management such as inspection of illegal buildings in green belt or update of GIS database. Moreover, the data acquis...
In this paper we combine the ideas of image matching, object detection, image retrieval and zero-shot learning for stating and solving the semantic matching problem. Semantic matcher takes two images ...
For the interpretation of point clouds, the semantic definition of extracted segments from point clouds or images is a common problem. Usually, the semantic of geometrical pre-segmented point cloud el...
While big data has been a topic of research and industry activity, much of it has been focused on unstructured data such as web logs, web crawl data, and social media data. One area which has received...
In recent years, the developments for Fully Convolutional Networks (FCN) have led to great improvements for semantic segmentation in various applications including fused remote sensing data. There is,...
In this paper, the problem of automatic detection of tuberculosis lesion on 3D lung CT images is considered as a benchmark for testing out algorithms based on a modern concept of Deep Learning. For tr...

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