Convolutional neural networks (CNNs) have recently exhibited an excellent performance in
hyperspectral image classification tasks. However, the straightforward CNN-based network …

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 …

The profound impact of deep learning and particularly of convolutional neural networks
(CNNs) in automatic image processing has been decisive for the progress and evolution of …

Deep learning techniques have boosted the performance of hyperspectral image (HSI)
classification. In particular, convolutional neural networks (CNNs) have shown superior …

Over the past few years, hyperspectral image classification using convolutional neural
networks (CNNs) has progressed significantly. In spite of their effectiveness, given that …

Convolutional neural networks (CNNs) have recently shown outstanding capability for
hyperspectral image (HSI) classification. In this work, a novel CNN model is proposed, which …

Convolutional neural networks (CNNs) showed impressive performance for hyperspectral
image (HSI) classification. Nevertheless, convolutional layers contain massive parameters …

In this letter, an alternative data-driven HSI classification model based on CapsNet is
proposed rather than recently predominant convolutional neural network (CNN)-based …

Capsule networks can be considered to be the next era of deep learning and have recently
shown their advantages in supervised classification. Instead of using scalar values to …

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