Change detection based on artificial intelligence: State-of-the-art and challenges
Change detection based on remote sensing (RS) data is an important method of detecting
changes on the Earth's surface and has a wide range of applications in urban planning …
changes on the Earth's surface and has a wide range of applications in urban planning …
Linking points with labels in 3D: A review of point cloud semantic segmentation
Ripe with possibilities offered by deep-learning techniques and useful in applications
related to remote sensing, computer vision, and robotics, 3D point cloud semantic …
related to remote sensing, computer vision, and robotics, 3D point cloud semantic …
A spatial-temporal attention-based method and a new dataset for remote sensing image change detection
Remote sensing image change detection (CD) is done to identify desired significant
changes between bitemporal images. Given two co-registered images taken at different …
changes between bitemporal images. Given two co-registered images taken at different …
PGA-SiamNet: Pyramid feature-based attention-guided Siamese network for remote sensing orthoimagery building change detection
In recent years, building change detection has made remarkable progress through using
deep learning. The core problems of this technique are the need for additional data (eg …
deep learning. The core problems of this technique are the need for additional data (eg …
An automatic change detection method for monitoring newly constructed building areas using time-series multi-view high-resolution optical satellite images
Automatically monitoring newly constructed building areas (NCBAs) is essential for efficient
land resource management and sustainable urban development, particularly in the rapidly …
land resource management and sustainable urban development, particularly in the rapidly …
Surveying coastal cliffs using two UAV platforms (multirotor and fixed-wing) and three different approaches for the estimation of volumetric changes
Á Gómez-Gutiérrez, GR Gonçalves - International Journal of …, 2020 - Taylor & Francis
The increasing availability of highly detailed and accurate three-dimensional (3D)
geospatial data are currently pushing the 3D change detection analysis towards a new 3D …
geospatial data are currently pushing the 3D change detection analysis towards a new 3D …
Extraction of urban building damage using spectral, height and corner information from VHR satellite images and airborne LiDAR data
X Wang, P Li - ISPRS Journal of Photogrammetry and Remote …, 2020 - Elsevier
Earth observation-based damage assessment has been widely studied in recent years.
Considering that the height and spatial variability of buildings change significantly in …
Considering that the height and spatial variability of buildings change significantly in …
A multikernel domain adaptation method for unsupervised transfer learning on cross-source and cross-region remote sensing data classification
Labeling remote sensing data for classification is labor-intensive and time-consuming.
Transfer learning (TL), under such context, is attracting increasing attention as it aims to …
Transfer learning (TL), under such context, is attracting increasing attention as it aims to …
Height estimation from single aerial images using a deep ordinal regression network
Understanding the 3-D geometric structure of the Earth's surface has been an active
research topic in photogrammetry and remote sensing community for decades, serving as …
research topic in photogrammetry and remote sensing community for decades, serving as …
LiDAR-guided dense matching for detecting changes and updating of buildings in Airborne LiDAR data
Change detection is essential to keep 3D city models up-to-date. LiDAR data with high
accuracy are used to create 3D city models. However, updating LiDAR data at state or …
accuracy are used to create 3D city models. However, updating LiDAR data at state or …