Dimensionality Reduction of Hyperspectral Imagery Based on Spatial-spectral Manifold Learning

no code implementations • 22 Dec 2018 • Hong Huang, Guangyao Shi, Haibo He, Yule Duan, Fulin Luo

However, a major challenge of GE is how to choose proper neighbors for graph construction and explore the spatial information of HSI data.

Classification Dimensionality Reduction +3

DLIMD: Dictionary Learning based Image-domain Material Decomposition for spectral CT

no code implementations • 6 May 2019 • Weiwen Wu, Haijun Yu, Peijun Chen, Fulin Luo, Fenglin Liu, Qian Wang, Yining Zhu, Yanbo Zhang, Jian Feng, Hengyong Yu

Second, we employ the direct inversion (DI) method to obtain initial material decomposition results, and a set of image patches are extracted from the mode-1 unfolding of normalized material image tensor to train a united dictionary by the K-SVD technique.

Computed Tomography (CT) Dictionary Learning +1

SGEN: Single-cell Sequencing Graph Self-supervised Embedding Network

no code implementations • 15 Oct 2021 • Ziyi Liu, Minghui Liao, Fulin Luo, Bo Du

This method constructs the graph by the similarity relationship between cells and adopts GCN to analyze the neighbor embedding information of samples, which makes the similar cell closer to each other on the 2D scatter plot.

Dimensionality Reduction Graph Embedding