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Graph Signal Processing for Heterogeneous Change Detection Part II: Spectral Domain Analysis
Then, we propose a regression model for the HCD, which decomposes the source signal into the regressed signal and changed signal, and requires the regressed signal have the same spectral property as the target signal on the same graph.
Graph Signal Processing for Heterogeneous Change Detection Part I: Vertex Domain Filtering
In this first part, we analyze the HCD with GSP from the vertex domain.
A Dual Neighborhood Hypergraph Neural Network for Change Detection in VHR Remote Sensing Images
To address this limitation, a dual neighborhood hypergraph neural network is proposed in this article, which combines the multiscale superpixel segmentation and hypergraph convolution to model and exploit the complex relationships.
Cooperative Multi-Agent Reinforcement Learning Based Distributed Dynamic Spectrum Access in Cognitive Radio Networks
With the development of the 5G and Internet of Things, amounts of wireless devices need to share the limited spectrum resources.
Multi-agent Reinforcement Learning
Reinforcement Learning (RL)
A Multiscale Graph Convolutional Network for Change Detection in Homogeneous and Heterogeneous Remote Sensing Images
In this paper, a novel CD method based on the graph convolutional network (GCN) and multiscale object-based technique is proposed for both homogeneous and heterogeneous images.
Adaptive Local Structure Consistency based Heterogeneous Remote Sensing Change Detection
To address this challenge, we explore an unsupervised change detection method based on adaptive local structure consistency (ALSC) between heterogeneous images in this letter, which constructs an adaptive graph representing the local structure for each patch in one image domain and then projects this graph to the other image domain to measure the change level.
Image reconstruction from few views by L0-norm optimization
As the L1-norm TV regularization is tending to uniformly penalize the image gradient and the low-contrast structures are sometimes over smoothed, we proposed a new algorithm based on the L0-norm of the GMI to deal with the few views problem.
An iterative algorithm for computed tomography image reconstruction from limited-angle projections
And the algorithm introduces scaling factors to control the two processes, respectively.
