332 citations · 771 across the 5 of their papers we have counts for
5 papers
Large-Scale Hyperspectral Image Clustering Using Contrastive Learning
Yaoming Cai, Zijia Zhang, Yan Liu +4
Clustering of hyperspectral images is a fundamental but challenging task. The recent development of hyperspectral image clustering has evolved from shallow models to deep and achie…
Fully Linear Graph Convolutional Networks for Semi-Supervised Learning and Clustering
Yaoming Cai, Zijia Zhang, Zhihua Cai +3
This paper presents FLGC, a simple yet effective fully linear graph convolutional network for semi-supervised and unsupervised learning. Instead of using gradient descent, we train…
Graph Convolutional Subspace Clustering: A Robust Subspace Clustering Framework for Hyperspectral Image
Yaoming Cai, Zijia Zhang, Zhihua Cai +3
Hyperspectral image (HSI) clustering is a challenging task due to the high complexity of HSI data. Subspace clustering has been proven to be powerful for exploiting the intrinsic r…
BS-Nets: An End-to-End Framework For Band Selection of Hyperspectral Image
Yaoming Cai, Xiaobo Liu, Zhihua Cai
Hyperspectral image (HSI) consists of hundreds of continuous narrow bands with high spectral correlation, which would lead to the so-called Hughes phenomenon and the high computati…
SuperPCA: A Superpixelwise PCA Approach for Unsupervised Feature Extraction of Hyperspectral Imagery
Junjun Jiang, Jiayi Ma, Chen Chen +3
As an unsupervised dimensionality reduction method, principal component analysis (PCA) has been widely considered as an efficient and effective preprocessing step for hyperspectral…