They are then individually fed into a multiview shared graph autoencoder, where clustering labels guide the learning of latent representations and the coefficient matrix. Furthermore, the proposed ...

Spectral unmixing is an important technique in remote sensing for analyzing hyperspectral images to identify endmembers and estimate fractional abundance maps. Over the past few decades, significant ...

Spectral Unmixing is an important technique in remote sensing for analyzing hyperspectral images to identify endmembers and estimate fractional abundance maps. Over the past few decades, significant ...

Integrating multi-source monitoring data and deep convolutional autoencoder ... results of the trained model on both the training and validation datasets were collected and visualized using a bar ...