Deep learning-based change detection in remote sensing images: A review
Images gathered from different satellites are vastly available these days due to the fast
development of remote sensing (RS) technology. These images significantly enhance the …
development of remote sensing (RS) technology. These images significantly enhance the …
Intelligent fruit yield estimation for orchards using deep learning based semantic segmentation techniques—a review
Smart farming employs intelligent systems for every domain of agriculture to obtain
sustainable economic growth with the available resources using advanced technologies …
sustainable economic growth with the available resources using advanced technologies …
Spectral–spatial–temporal transformers for hyperspectral image change detection
Convolutional neural networks (CNNs) with excellent spatial feature extraction abilities have
become popular in remote sensing (RS) image change detection (CD). However, CNNs …
become popular in remote sensing (RS) image change detection (CD). However, CNNs …
Hyperspectral change detection based on multiple morphological profiles
With the increasing availability of multitemporal hyperspectral imagery, hyperspectral
change detection under heterogeneous backgrounds is a challenging task. Due to the …
change detection under heterogeneous backgrounds is a challenging task. Due to the …
Spatial-contextual information utilization framework for land cover change detection with hyperspectral remote sensed images
Land cover change detection (LCCD) using bitemporal remote sensing images is a crucial
task for identifying the change areas on the Earth's surface. However, the utilization of …
task for identifying the change areas on the Earth's surface. However, the utilization of …
A new end-to-end multi-dimensional CNN framework for land cover/land use change detection in multi-source remote sensing datasets
ST Seydi, M Hasanlou, M Amani - Remote Sensing, 2020 - mdpi.com
The diversity of change detection (CD) methods and the limitations in generalizing these
techniques using different types of remote sensing datasets over various study areas have …
techniques using different types of remote sensing datasets over various study areas have …
Three-order tucker decomposition and reconstruction detector for unsupervised hyperspectral change detection
Change detection from multitemporal hyperspectral images has attracted great attention.
Most traditional methods using spectral information for change detection treat a …
Most traditional methods using spectral information for change detection treat a …
Multispectral and hyperspectral images based land use/land cover change prediction analysis: an extensive review
MS Navin, L Agilandeeswari - Multimedia Tools and Applications, 2020 - Springer
Research in the field of remote sensing attracts attention among researchers all over the
world. From different remote sensing applications, the problem on Land Use/Land Cover …
world. From different remote sensing applications, the problem on Land Use/Land Cover …
Multilayer cascade screening strategy for semi-supervised change detection in hyperspectral images
Change detection (CD) is an important application of remote sensing, which provides
information about land cover changes on the Earth's surface. Hyperspectral image (HSI) can …
information about land cover changes on the Earth's surface. Hyperspectral image (HSI) can …
Self-structured pyramid network with parallel spatial-channel attention for change detection in VHR remote sensed imagery
Land cover change detection (CD) in very-high-resolution (VHR) images is still impeded by
weak pattern separability and land cover complexity. To address these challenges, a self …
weak pattern separability and land cover complexity. To address these challenges, a self …