Deep learning-based semantic segmentation of urban features in satellite images: A review and meta-analysis
Availability of very high-resolution remote sensing images and advancement of deep
learning methods have shifted the paradigm of image classification from pixel-based and …
learning methods have shifted the paradigm of image classification from pixel-based and …
Using satellite imagery to understand and promote sustainable development
BACKGROUND Accurate and comprehensive measurements of a range of sustainable
development outcomes are fundamental inputs into both research and policy. For instance …
development outcomes are fundamental inputs into both research and policy. For instance …
Semantic segmentation of water bodies in very high-resolution satellite and aerial images
M Wieland, S Martinis, R Kiefl, V Gstaiger - Remote Sensing of …, 2023 - Elsevier
This study evaluates the performance of convolutional neural networks for semantic
segmentation of water bodies in very high-resolution satellite and aerial images from …
segmentation of water bodies in very high-resolution satellite and aerial images from …
LANet: Local attention embedding to improve the semantic segmentation of remote sensing images
The trade-off between feature representation power and spatial localization accuracy is
crucial for the dense classification/semantic segmentation of remote sensing images (RSIs) …
crucial for the dense classification/semantic segmentation of remote sensing images (RSIs) …
A survey on green deep learning
Object detection and image segmentation with deep learning on Earth observation data: A review—Part II: Applications
In Earth observation (EO), large-scale land-surface dynamics are traditionally analyzed by
investigating aggregated classes. The increase in data with a very high spatial resolution …
investigating aggregated classes. The increase in data with a very high spatial resolution …
Pointflow: Flowing semantics through points for aerial image segmentation
Abstract Aerial Image Segmentation is a particular semantic segmentation problem and has
several challenging characteristics that general semantic segmentation does not have …
several challenging characteristics that general semantic segmentation does not have …
MANet: A multi-level aggregation network for semantic segmentation of high-resolution remote sensing images
B Chen, M **a, M Qian, J Huang - International Journal of Remote …, 2022 - Taylor & Francis
With the continuous improvement of the segmentation effect for natural datasets, some
studies have gradually been applied to high-resolution remote sensing images (HRRSIs) …
studies have gradually been applied to high-resolution remote sensing images (HRRSIs) …
From single-to multi-modal remote sensing imagery interpretation: A survey and taxonomy
Modality is a source or form of information. Through various modal information, humans can
perceive the world from multiple perspectives. Simultaneously, the observation of remote …
perceive the world from multiple perspectives. Simultaneously, the observation of remote …