Road Network Deterioration Monitoring Using Aerial Images and Computer Vision
Road maintenance is an essential process for guaranteeing the quality of transportation in any city. A crucial step towards effective road maintenance is the ability to update the inventory of the road network. We present a proof of concept of a protocol for maintaining said inventory based on the use of unmanned aerial vehicles to quickly collect images which are processed by a computer vision program that automatically identifies potholes and their severity. Our protocol aims to provide information to local governments to prioritise the road network maintenance budget, and to be able to detect early stages of road deterioration so as to minimise maintenance expenditure.
Code (0)
등록된 구현이 없습니다.
Similar Papers 제목 키워드 기반
Aerial image geolocalization from recognition and matching of roads and intersections
Aerial image analysis at a semantic level is important in many applications with strong potential impact in industry and consumer use, such as automated mapping, urban planning, real estate and environment monitoring, or…
LandCover.ai: Dataset for Automatic Mapping of Buildings, Woodlands, Water and Roads from Aerial Imagery
Monitoring of land cover and land use is crucial in natural resources management. Automatic visual mapping can carry enormous economic value for agriculture, forestry, or public administration. Satellite or aerial images…
Bird's-Eye View Semantic SegmentationChange DetectionManagementObject Detection In Aerial Images+2From underwater to aerial: a novel multi-scale knowledge distillation approach for coral reef monitoring
Drone-based remote sensing combined with AI-driven methodologies has shown great potential for accurate mapping and monitoring of coral reef ecosystems. This study presents a novel multi-scale approach to coral reef moni…
Knowledge DistillationCar Detection using Unmanned Aerial Vehicles: Comparison between Faster R-CNN and YOLOv3
Unmanned Aerial Vehicles are increasingly being used in surveillance and traffic monitoring thanks to their high mobility and ability to cover areas at different altitudes and locations. One of the major challenges is to…
Linear features segmentation from aerial images
The rapid development of remote sensing technologies have gained significant attention due to their ability to accurately localize, classify, and segment objects from aerial images. These technologies are commonly used i…
Segmentation