Lim, J.Z., Mountstephens, J. and Teo, J. (2022) Eye-Tracking Feature Extraction for Biometric Machine Learning. Frontiers in Neurorobotics, 15, Article ID 796895.

In the last decade, auxiliary information has been widely used to address data sparsity. Due to the advantages of feature extraction and the no-label requirement, autoencoder-based methods ...

In this letter, we discuss unsupervised feature extraction on hyperspectral imagery (HSI) and propose a novel approach based on autoencoder (AE) networks to extract spectral-spatial features from HSI.

Impact Statement: Autoencoder is a popular data-driven modeling technology in deep learning. It can deal with the nonlinear relationships among process variables, and has a powerful feature extraction ...