S2HM2: A Spectral-Spatial Hierarchical Masked Modeling Framework for Self-Supervised Feature Learning and Classification of Large-Scale Hyperspectral Images

Most of the existing deep learning-based hyperspectral image (HSI) classification algorithms are based on supervised learning, where a large number of annotated labels with high acquisition cost are required. Self-supervised learning (SSL) methods can learn abundant representations using a large amo...

Ausführliche Beschreibung