Building and road extraction from remote sensing images is of great significance to urban planning. At present, most building models adopt deep learning semantic segmentation method. However, the existing methods did not pay enough attention feature information between hidden layers, which led neglect category context pixels in pixel classification, resulting these two problems large-scale misj...

This paper introduces an innovative road network extraction algorithm using synthetic aperture radar (SAR) imagery for improving the accuracy of road extraction. The state-of-the-art approaches, such as fraction extraction and road network optimization, failed to obtain continuous road segments in separate successions, since the optimization could not change the parts ignored by the fraction ex...

—Roads represent a pervasive feature on most landscapes that can pose multiple threats to wildlife populations and substantial challenges for management. To be effective, management strategies must often target where threats are most concentrated. Road mortality and nest predation are well-documented threats to Diamondbacked Terrapins (Malaclemys terrapin) across the majority of their range, in...

An important feature in most urban roads, and similar environments such as in theme parks, campus sites, industrial estates, science parks and the like is the existence of pavements or curbs on either side defining the road boundaries. These curbs, which are mostly parallel to the road, can be harnessed to extract useful features of the road for implementing autonomous navigation or driver assi...

In today’s world automobile industries are coming out with so many new features in cars. Road infrastructures are also getting much better in all over the world. Due to this, the number of road accidents has increased and more number of people are dying in it. Researchers have tried to solve this problem by using virtual driver feature in the car. A computer vision based road detection and navi...

The road coloring problem is an interesing problem proposed over 40 years ago by Adler, Goodwyn and Weiss. Hundreds of mathematicians worked on this problem and failed to make the conjecture a theorem. Finally, in 2007, it was proved by a 60-year-old Israeli mathematician, Avraham Trahtman. It turns out the prove was quite simple after Trahtman partitioned the graph into cycles and trees. The d...

This paper aims at improving two main uncertain factors in neural networks training in developing a composite road safety performance indicator. These factors are the initial value of network weights and the iteration time. More specially, rough sets theory is applied for rule induction and feature selection in decision situations, and the concepts of reduct and core are utilized to generate de...

This chapter is concerned with the problem of estimating a map of the immediate surroundings of a vehicle as it moves. In order to compute these map estimates sensor measurements from radars, lasers and/or cameras are used together with the standard proprioceptive sensors present in a car. Four different types of maps are discussed. Feature based maps are represented by a set of salient feature...

Scene understanding for autonomous vehicles is a challenging computer vision task, with recent advances in convolutional neural networks (CNNs) achieving results that notably surpass prior traditional feature driven approaches. However, limited work investigates the application of such methods either within the highly unstructured off-road environment or to RGBD input data. In this work, we tak...