Owing to the powerful data representation ability of deep learning (DL) techniques,
tremendous progress has been recently made in hyperspectral image (HSI) classification …

Deep neural networks (DNNs) have emerged as a relevant tool for the classification of
remotely sensed hyperspectral images (HSIs), with convolutional neural networks (CNNs) …

Deep learning-based hyperspectral image (HSI) classification has attracted more and more
attention because of its excellent classification ability. Generally, the outstanding …

Deep learning has recently attracted significant attention in the field of hyperspectral images
(HSIs) classification. However, the construction of an efficient deep neural network mostly …

Deep neural network has been extensively applied to hyperspectral image (HSI)
classification recently. However, its success is greatly attributed to numerous labeled …

Due to its remarkable feature representation capability and high performance, convolutional
neural networks (CNN) have emerged as a popular choice for hyperspectral image (HSI) …

Deep learning methods have shown their marvel performance on hyperspectral image (HSI)
classification tasks. In particular, algorithms based on convolution neural network (CNN) …

Convolutional neural networks (CNNs) exhibit good performance in image processing tasks,
pointing themselves as the current state-of-the-art of deep learning methods. However, the …

Convolutional neural networks (CNNs) have been extensively studied for hyperspectral
image classification (HSIC). However, CNNs are critically attributed to a large number of …

Deep convolutional networks have been extensively deployed in hyperspectral image (HSI)
classification. Reaching for high accuracy, the existing deep-learning-based methods …