Recent imaging science and technology discoveries have considered hyperspectral
imagery and remote sensing. The current intelligent technologies, such as support vector …

Abstract Generative Adversarial Networks (GANs) are one of the most creative advances in
Deep Learning (DL) in recent years. The Remote Sensing (RS) community has adopted …

Deep learning has achieved great success in hyperspectral image classification. However,
when processing new hyperspectral images, the existing deep learning models must be …

Recently, deep learning-based hyperspectral image (HSI) classification techniques are
flourishing and exhibit good performance, where cross-domain information is usually utilized …

Band selection is an important step in efficient processing of hyperspectral images (HSIs),
which can be seen as the combination of powerful band search technique and effective …

Coastal wetlands are main components of the “blue carbon” ecosystems in coastal zones.
Salt-marsh biomass is especially important regarding climate-change mitigation. Generating …

Deep neural networks have attained great success in handling high dimensional data,
especially images. However, generating naturalistic images containing ginormous subjects …

Generative adversarial network (GAN) has been rapidly developed because of its powerful
generating ability. However, imbalanced class distribution of hyperspectral images (HSIs) …

With the rise of deep learning, the combination of spectroscopy analysis techniques and
deep learning methods has been extensively utilized in the field of agriculture, such as the …

The past decade has witnessed the rising dominance of deep learning and artificial
intelligence in a wide range of applications. In particular, the ocean of wireless smartphones …