[HTML][HTML] Algorithmic urban planning for smart and sustainable development: Systematic review of the literature
In recent years, artificial intelligence (AI) has been increasingly put into use to address cities'
economic, social, environmental, and governance challenges. Thanks to its advanced …
economic, social, environmental, and governance challenges. Thanks to its advanced …
Effect of attention mechanism in deep learning-based remote sensing image processing: A systematic literature review
Machine learning, particularly deep learning (DL), has become a central and state-of-the-art
method for several computer vision applications and remote sensing (RS) image …
method for several computer vision applications and remote sensing (RS) image …
ResUNet-a: A deep learning framework for semantic segmentation of remotely sensed data
Scene understanding of high resolution aerial images is of great importance for the task of
automated monitoring in various remote sensing applications. Due to the large within-class …
automated monitoring in various remote sensing applications. Due to the large within-class …
Change detection in multisource VHR images via deep siamese convolutional multiple-layers recurrent neural network
With the rapid development of Earth observation technology, very-high-resolution (VHR)
images from various satellite sensors are more available, which greatly enrich the data …
images from various satellite sensors are more available, which greatly enrich the data …
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 …
Building extraction from remote sensing images with sparse token transformers
Deep learning methods have achieved considerable progress in remote sensing image
building extraction. Most building extraction methods are based on Convolutional Neural …
building extraction. Most building extraction methods are based on Convolutional Neural …
Semantic segmentation-based building footprint extraction using very high-resolution satellite images and multi-source GIS data
Automatic extraction of building footprints from high-resolution satellite imagery has become
an important and challenging research issue receiving greater attention. Many recent …
an important and challenging research issue receiving greater attention. Many recent …
BOMSC-Net: Boundary optimization and multi-scale context awareness based building extraction from high-resolution remote sensing imagery
Automatic building extraction from high-resolution remote sensing imagery has various
applications, such as urban planning and land use management. However, the existing …
applications, such as urban planning and land use management. However, the existing …
Joint semantic–geometric learning for polygonal building segmentation from high-resolution remote sensing images
As a fundamental task for geographical information updating, 3D city modeling, and other
critical applications, the automatic extraction of building footprints from high-resolution …
critical applications, the automatic extraction of building footprints from high-resolution …
Stacked autoencoders driven by semi-supervised learning for building extraction from near infrared remote sensing imagery
In this paper, we propose a Stack Auto-encoder (SAE)-Driven and Semi-Supervised (SSL)-
Based Deep Neural Network (DNN) to extract buildings from relatively low-cost satellite near …
Based Deep Neural Network (DNN) to extract buildings from relatively low-cost satellite near …