[HTML][HTML] Deep learning classifiers for hyperspectral imaging: A review
Advances in computing technology have fostered the development of new and powerful
deep learning (DL) techniques, which have demonstrated promising results in a wide range …
deep learning (DL) techniques, which have demonstrated promising results in a wide range …
Comprehensive survey of deep learning in remote sensing: theories, tools, and challenges for the community
In recent years, deep learning (DL), a rebranding of neural networks (NNs), has risen to the
top in numerous areas, namely computer vision (CV), speech recognition, and natural …
top in numerous areas, namely computer vision (CV), speech recognition, and natural …
Hyperspectral image classification using group-aware hierarchical transformer
S Mei, C Song, M Ma, F Xu - IEEE Transactions on Geoscience …, 2022 - ieeexplore.ieee.org
Hyperspectral image (HSI) classification is a critical task with numerous applications in the
field of remote sensing. Although convolutional neural networks have achieved remarkable …
field of remote sensing. Although convolutional neural networks have achieved remarkable …
Deep pyramidal residual networks for spectral–spatial hyperspectral image classification
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 …
pointing themselves as the current state-of-the-art of deep learning methods. However, the …
Improved transformer net for hyperspectral image classification
Y Qing, W Liu, L Feng, W Gao - Remote Sensing, 2021 - mdpi.com
In recent years, deep learning has been successfully applied to hyperspectral image
classification (HSI) problems, with several convolutional neural network (CNN) based …
classification (HSI) problems, with several convolutional neural network (CNN) based …
Deep learning for remote sensing image classification: A survey
Remote sensing (RS) image classification plays an important role in the earth observation
technology using RS data, having been widely exploited in both military and civil fields …
technology using RS data, having been widely exploited in both military and civil fields …
Multi-scale 3D deep convolutional neural network for hyperspectral image classification
Research in deep neural network (DNN) and deep learning has great progress for 1D
(speech), 2D (image) and 3D (3D-object) recognition/classification problems. As HSI that …
(speech), 2D (image) and 3D (3D-object) recognition/classification problems. As HSI that …
Feature extraction with multiscale covariance maps for hyperspectral image classification
The classification of hyperspectral images (HSIs) using convolutional neural networks
(CNNs) has recently drawn significant attention. However, it is important to address the …
(CNNs) has recently drawn significant attention. However, it is important to address the …
Hyperspectral and lidar data applied to the urban land cover machine learning and neural-network-based classification: A review
Rapid technological advances in airborne hyperspectral and lidar systems paved the way
for using machine learning algorithms to map urban environments. Both hyperspectral and …
for using machine learning algorithms to map urban environments. Both hyperspectral and …
Hyperspectral classification based on lightweight 3-D-CNN with transfer learning
Recently, hyperspectral image (HSI) classification approaches based on deep learning (DL)
models have been proposed and shown promising performance. However, because of very …
models have been proposed and shown promising performance. However, because of very …