Artificial intelligence for remote sensing data analysis: A review of challenges and opportunities
Artificial intelligence (AI) plays a growing role in remote sensing (RS). Applications of AI,
particularly machine learning algorithms, range from initial image processing to high-level …
particularly machine learning algorithms, range from initial image processing to high-level …
Segmentation for Object-Based Image Analysis (OBIA): A review of algorithms and challenges from remote sensing perspective
MD Hossain, D Chen - ISPRS Journal of Photogrammetry and Remote …, 2019 - Elsevier
Image segmentation is a critical and important step in (GEographic) Object-Based Image
Analysis (GEOBIA or OBIA). The final feature extraction and classification in OBIA is highly …
Analysis (GEOBIA or OBIA). The final feature extraction and classification in OBIA is highly …
Swin transformer embedding UNet for remote sensing image semantic segmentation
Global context information is essential for the semantic segmentation of remote sensing (RS)
images. However, most existing methods rely on a convolutional neural network (CNN) …
images. However, most existing methods rely on a convolutional neural network (CNN) …
Object-contextual representations for semantic segmentation
In this paper, we study the context aggregation problem in semantic segmentation.
Motivated by that the label of a pixel is the category of the object that the pixel belongs to, we …
Motivated by that the label of a pixel is the category of the object that the pixel belongs to, we …
Semantics for robotic mapping, perception and interaction: A survey
For robots to navigate and interact more richly with the world around them, they will likely
require a deeper understanding of the world in which they operate. In robotics and related …
require a deeper understanding of the world in which they operate. In robotics and related …
UAVid: A semantic segmentation dataset for UAV imagery
Semantic segmentation has been one of the leading research interests in computer vision
recently. It serves as a perception foundation for many fields, such as robotics and …
recently. It serves as a perception foundation for many fields, such as robotics and …
On creating benchmark dataset for aerial image interpretation: Reviews, guidances, and million-aid
The past years have witnessed great progress on remote sensing (RS) image interpretation
and its wide applications. With RS images becoming more accessible than ever before …
and its wide applications. With RS images becoming more accessible than ever before …
Syndrone-multi-modal uav dataset for urban scenarios
The development of computer vision algorithms for Unmanned Aerial Vehicles (UAVs)
imagery heavily relies on the availability of annotated high-resolution aerial data. However …
imagery heavily relies on the availability of annotated high-resolution aerial data. However …
A comprehensive review for typical applications based upon unmanned aerial vehicle platform
Unmanned aerial vehicles (UAVs) have been widely applied in military and civilian fields
due to their flexibility and effectiveness. As a vital component of UAVs, the vision system has …
due to their flexibility and effectiveness. As a vital component of UAVs, the vision system has …
Drone image segmentation using machine and deep learning for mapping raised bog vegetation communities
The application of drones has recently revolutionised the mapping of wetlands due to their
high spatial resolution and the flexibility in capturing images. In this study, the drone imagery …
high spatial resolution and the flexibility in capturing images. In this study, the drone imagery …