Yun Cao

TL;DR: A novel unsupervised feature learning method called latent relationship guided the stacked sparse autoencoder (LRSSAE) is developed in this article, which can effectively exploit the latent relationship under feature space to improve the ability of feature learning.

TL;DR: In this article, the authors provide a thorough review of recent achievements in the field of land-use mapping using deep learning (DL) algorithms, which offer novel opportunities for the development of LUM for HSR-RSIs.

TL;DR: Zhang et al. as discussed by the authors developed a deep metric learning approach with generative adversarial network regularization (DML-GANR) for HSR-RSI retrieval.

TL;DR: A deep metric learning approach with generative adversarial network regularization (DML-GANR) with superior performance over state-of-the-art techniques in HSR-RSI retrieval.

TL;DR: Wang et al. as mentioned in this paper proposed a deep feature learning with label consistencies (DFL-LC) method to realize hyperspectral images (HSIs) classification, which can effectively extract features from HSI data compared with other traditional hand-crafted methods.