This project focuses on learning useful representations from unlabelled data for downstream tasks, specifically categorizing images into one of N categories using Variational Autoencoders (VAE). The ...
Abstract: Modern industrial data is commonly collected under various working conditions, which are usually nonlinear and multi-modal. This poses great challenges to the accurate isolation of fault ...
Abstract: Deep learning-based informative band selection methods on hyperspectral images (HSIs) have recently gained intense attention to eliminate spectral correlation and redundancies. However, ...