With developments in deep learning, semantic segmentation of remote sensing images has
made great progress. Currently, mainstream methods are based on convolutional neural …

Semantic segmentation is a significant research topic for decades and has been employed
in several applications. In recent years, semantic segmentation has been focused on …

Semantic segmentation is one of the hot topics in the field of remote sensing image
intelligent analysis. Deep convolutional neural network (DCNN) has become a mainstream …

Localization in aerial imagery-based maps offers many advantages, such as global
consistency, geo-referenced maps, and the availability of publicly accessible data. However …

Accurate detection of pavement markings at the pixel level is crucial for enhancing traffic
safety. The majority of current advanced deep-learning networks predominantly focus on …

A variety of deep learning approaches have been applied to region of interest (ROI)
extraction, which is a fundamental task in the field of remote sensing image (RSI) …

Deep Learning (DL) based identification and detection of elements in urban spaces through
Earth Observation (EO) datasets have been widely researched and discussed. Such studies …

High-definition (HD) maps can provide precise road information that enables an
autonomous driving system to effectively navigate a vehicle. Recent research has focused …

High-definition (HD) maps offer precise positioning and dependable navigation capabilities,
which are essential to guarantee the safety of autonomous vehicles. Lane-level road …

There is presently a need for more robust navigation algorithms for autonomous industrial
vehicles. These have reasonably guaranteed the adequate reliability of the navigation. In …