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 …
Deep learning for change detection in remote sensing: a review
ABSTRACT A large number of publications have incorporated deep learning in the process
of remote sensing change detection. In these Deep Learning Change Detection (DLCD) …
of remote sensing change detection. In these Deep Learning Change Detection (DLCD) …
Analysis on change detection techniques for remote sensing applications: A review
Satellite images taken on the earth's surface are analyzed to identify the spatial and
temporal changes that have occurred naturally or manmade. Real-time prediction of change …
temporal changes that have occurred naturally or manmade. Real-time prediction of change …
Change detection in image time-series using unsupervised LSTM
Deep learning-based unsupervised change detection (CD) methods compare a prechange
and a postchange image in deep feature space and require precise knowledge of the event …
and a postchange image in deep feature space and require precise knowledge of the event …
Stacked autoencoders for multiclass change detection in hyperspectral images
Change detection (CD) in multitemporal datasets is a key task in remote sensing. In this
paper, a scheme to perform multiclass CD for remote sensing hyperspectral datasets …
paper, a scheme to perform multiclass CD for remote sensing hyperspectral datasets …
Fast reconstruction of non-uniform sampling multidimensional NMR spectroscopy via a deep neural network
Multidimensional nuclear magnetic resonance (NMR) spectroscopy is used to examine the
chemical structures of the studied systems. Unfortunately, the application of NMR spectra is …
chemical structures of the studied systems. Unfortunately, the application of NMR spectra is …
Diagnostic analysis on change vector analysis methods for LCCD using remote sensing images
Change vector analysis (CVA) is a simple yet attractive method to detect changes with
remote sensing images. Since its first introduction in 1980, CVA has received increased …
remote sensing images. Since its first introduction in 1980, CVA has received increased …
Authentication of underwater acoustic transmissions via machine learning techniques
We consider the problem of discriminating a legitimate transmitter from an impersonating
attacker in an underwater acoustic network under a physical layer security framework. In …
attacker in an underwater acoustic network under a physical layer security framework. In …
Deep learning-based homogeneous pixel selection for multitemporal SAR interferometry
J Hu, W Wu, R Gui, Z Li, J Zhu - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
Homogeneous pixel selection (HPS) plays an important role in the application of
multitemporal synthetic aperture radar interferometry (InSAR). The statistical goodness-of-fit …
multitemporal synthetic aperture radar interferometry (InSAR). The statistical goodness-of-fit …
Genesis of basic and multi-layer echo state network recurrent autoencoders for efficient data representations
It is a widely accepted fact that data representations intervene noticeably in machine
learning tools. The more they are well defined the better the performance results are …
learning tools. The more they are well defined the better the performance results are …