Multi-object segmentation in complex urban scenes from high-resolution remote sensing data
Terrestrial features extraction, such as roads and buildings from aerial images using an
automatic system, has many usages in an extensive range of fields, including disaster …
automatic system, has many usages in an extensive range of fields, including disaster …
A multiscale and multitask deep learning framework for automatic building extraction
J Yin, F Wu, Y Qiu, A Li, C Liu, X Gong - Remote Sensing, 2022 - mdpi.com
Detecting buildings, segmenting building footprints, and extracting building edges from high-
resolution remote sensing images are vital in applications such as urban planning, change …
resolution remote sensing images are vital in applications such as urban planning, change …
A framework integrating deeplabV3+, transfer learning, active learning, and incremental learning for mapping building footprints
Convolutional neural network (CNN)-based remote sensing (RS) image segmentation has
become a widely used method for building footprint mapping. Recently, DeeplabV3+, an …
become a widely used method for building footprint mapping. Recently, DeeplabV3+, an …
Fast building segmentation from satellite imagery and few local labels
Innovations in computer vision algorithms for satellite image analysis can enable us to
explore global challenges such as urbanization and land use change at the planetary level …
explore global challenges such as urbanization and land use change at the planetary level …
Semantic segmentation of satellite images with different building types using deep learning methods
In this study, using deep learning-based semantic segmentation methods, an automatic
building segmentation application was carried out with a remote sensing image on a sample …
building segmentation application was carried out with a remote sensing image on a sample …
Unsupervised building extraction from multimodal aerial data based on accurate vegetation removal and image feature consistency constraint
Accurate building extraction from remotely sensed data is difficult to perform automatically
because of the complex environments and the complex shapes, colours and textures of …
because of the complex environments and the complex shapes, colours and textures of …
A Sparse Sharing Multi-task Framework for Building Footprint Extraction from Remote Sensing Imagery Following the Dual Lottery Ticket Hypothesis
Building footprint extraction from high-resolution remote sensing imagery is significant for
urban planning, change detection, disaster management, and other applications. Recently …
urban planning, change detection, disaster management, and other applications. Recently …
A Multi-Feature Fusion Framework Based on DS Theory for Automatic Building Extraction From High-Resolution Remote Sensing Imagery
X Zhang, X Li, J Huang, E Li, W Liu… - IEEE Journal of …, 2024 - ieeexplore.ieee.org
Building information serves as a critical foundational dataset in the fields of urban planning,
smart cities and surveying and mapping, and high-resolution remote sensing (HRRS) …
smart cities and surveying and mapping, and high-resolution remote sensing (HRRS) …
Multi-step feature fusion for natural disaster damage assessment on satellite images
M Żarski, JA Miszczak - IEEE Access, 2024 - ieeexplore.ieee.org
Quick and accurate assessment of the damage state of buildings after natural disasters is
crucial for undertaking properly targeted rescue and subsequent recovery operations, which …
crucial for undertaking properly targeted rescue and subsequent recovery operations, which …
Hierarchical disentangling network for building extraction from very high resolution optical remote sensing imagery
Building extraction using very high resolution (VHR) optical remote sensing imagery is an
essential interpretation task that impacts human life. However, buildings in different …
essential interpretation task that impacts human life. However, buildings in different …