Methods and datasets on semantic segmentation for Unmanned Aerial Vehicle remote sensing images: A review
Abstract Unmanned Aerial Vehicle (UAV) has seen a dramatic rise in popularity for remote-
sensing image acquisition and analysis in recent years. It has brought promising results in …
sensing image acquisition and analysis in recent years. It has brought promising results in …
Superpixel-based multiscale CNN approach toward multiclass object segmentation from UAV-captured aerial images
Unmanned aerial vehicles (UAVs) are promising remote sensors capable of reforming
remote sensing applications. However, for artificial-intelligence-guided tasks, such as land …
remote sensing applications. However, for artificial-intelligence-guided tasks, such as land …
A lightweight deep learning architecture for vegetation segmentation using UAV-captured aerial images
The unmanned aerial vehicle (UAV)-captured panoptic remote sensing images have great
potential to promote robotics-inspired intelligent solutions for land cover mapping, disaster …
potential to promote robotics-inspired intelligent solutions for land cover mapping, disaster …
Vegetation extraction from UAV-based aerial images through deep learning
The panoptic aerial images of the earth's surface captured by satellites and unmanned
aerial vehicles (UAVs) have great potential to support applications in various domains …
aerial vehicles (UAVs) have great potential to support applications in various domains …
Research progress on deep learning methods for object detection and semantic segmentation in UAV aerial images
LUO Xudong, WU Yiquan, C Jinlin - Acta Aeronautica et Astronautica …, 2024 - sciopen.com
Abstract Unmanned Aerial Vehicles (UAV) have been widely used due to their advantages
of small size, light weight, and simple operation. The combination of the deep learning …
of small size, light weight, and simple operation. The combination of the deep learning …
UnetEdge: A transfer learning-based framework for road feature segmentation from high-resolution remote sensing images
Topological information is a crucial factor affecting road feature extraction using semantic
segmentation. Many segmentation models have recently been developed for road feature …
segmentation. Many segmentation models have recently been developed for road feature …
A lightweight multiscale-multiobject deep segmentation architecture for UAV-based consumer applications
Smart UAVs have been developed under the consumer Internet of Drone Things (CIoDTs)
framework to improve the quality of service (QoS) for several commercial and consumer …
framework to improve the quality of service (QoS) for several commercial and consumer …
Extraction of Roads Using the Archimedes Tuning Process with the Quantum Dilated Convolutional Neural Network
Road network extraction is a significant challenge in remote sensing (RS). Automated
techniques for interpreting RS imagery offer a cost-effective solution for obtaining road …
techniques for interpreting RS imagery offer a cost-effective solution for obtaining road …
Satellite IoT based road extraction from VHR images through superpixel-CNN architecture
In the past few decades, technology has progressively become ineluctable in human lives,
primarily due to the growth of certain fields like space technology, Big Data, the Internet of …
primarily due to the growth of certain fields like space technology, Big Data, the Internet of …
Archimedes optimisation algorithm quantum dilated convolutional neural network for road extraction in remote sensing images
AMS Sundarapandi, Y Alotaibi, T Thanarajan… - Heliyon, 2024 - cell.com
Roads are closely intertwined with human existence, and the process of extracting road
networks has emerged as the most prominent task in remote sensing (RS). The automated …
networks has emerged as the most prominent task in remote sensing (RS). The automated …