Road segmentation from remote sensing images is an important task in many applications. However, due to the high density of roads and complex background, are often occluded by trees. This makes accurate road a challenge task. Most existing networks rely on convolutions with small kernels; however, these methods cannot obtain satisfying results because long-range dependencies not captured intrin...

We constructed a GF-3 SAR image dataset based on road segmentation to boost the development of synthetic aperture radar (SAR) technology and make images be applied practice better. selected 23 scenes in Shaanxi, China, cut them into chips with 512 × pixels, then labeled using LabelMe labeling tool. The consists 10026 chips, these are from different imaging modes, so there is diversity resolutio...

Many studies on the semantic segmentation of cracks using machine learning (ML) technique can be found in relevant literature. To date, results obtained are quite good, but often accuracy trained model and evaluated traditional metrics only, most cases, goal is to detect only occurrence cracks. Particular attention should paid thickness segmented crack since, road pavement maintenance, width ma...

This paper describes a real-time road following and road junction detection vision system for autonomous vehicles. Vision-guided road following requires extracting road boundaries from images in real-time to guide the navigation of autonomous vehicles on the roadway. We use a histogram-based pixel classification algorithm to classify road and non-road regions in the image. The most likely road ...