The performance of semantic segmentation in high-resolution aerial imagery has been
improved rapidly through the introduction of deep fully convolutional neural network (FCN) …

Unmanned Aerial Vehicles (UAVs) have been employed for multiple tasks in the last
decade, including planetary exploration. A common task for UAVs is mapping, with maps …

Drone perception systems use information from sensor fusion to perform tasks like object
detection and tracking, visual localization and mapping, trajectory planning, and …

Automatic building extraction from aerial imagery has several applications in urban
planning, disaster management, and change detection. In recent years, several works have …

Semantic segmentation of images enables pixel-wise scene understanding which in turn is
a critical component for tasks such as autonomous driving. While recent implementations of …

Semantic segmentation is one of the fundamental tasks in understanding high-resolution
aerial images. Recently, convolutional neural network (CNN) and fully convolutional network …

The semantic segmentation of drone LiDAR data is important in intelligent industrial
operation and maintenance. However, current methods are not effective in directly …

Semantic segmentation plays a crucial role in enabling intelligent vehicles to perceive and
understand their surroundings. However, datasets used for semantic segmentation often …

Recently, neural architecture search (NAS) has gained a lot of attention as a tool for
constructing deep neural networks automatically. NAS methods have successfully found …

Semantic segmentation based on deep learning has undergone remarkable advancements
in recent years. However, due to the neglect of the shallow features, the problems of …