[HTML][HTML] Deep learning for land use and land cover classification based on hyperspectral and multispectral earth observation data: A review
Lately, with deep learning outpacing the other machine learning techniques in classifying
images, we have witnessed a growing interest of the remote sensing community in …
images, we have witnessed a growing interest of the remote sensing community in …
Hyperspectral image classification: Potentials, challenges, and future directions
Recent imaging science and technology discoveries have considered hyperspectral
imagery and remote sensing. The current intelligent technologies, such as support vector …
imagery and remote sensing. The current intelligent technologies, such as support vector …
Land Use and Land Cover Classification with Hyperspectral Data: A comprehensive review of methods, challenges and future directions
MA Moharram, DM Sundaram - Neurocomputing, 2023 - Elsevier
Recently, many efforts have been concentrated on land use land cover (LULC) classification
due to rapid urbanization, environmental pollution, agriculture drought, frequent floods, and …
due to rapid urbanization, environmental pollution, agriculture drought, frequent floods, and …
[HTML][HTML] Deep learning for land cover classification using only a few bands
There is an emerging interest in using hyperspectral data for land cover classification. The
motivation behind using hyperspectral data is the notion that increasing the number of …
motivation behind using hyperspectral data is the notion that increasing the number of …
BASS net: Band-adaptive spectral-spatial feature learning neural network for hyperspectral image classification
Deep learning based land cover classification algorithms have recently been proposed in
the literature. In hyperspectral images (HSIs), they face the challenges of large …
the literature. In hyperspectral images (HSIs), they face the challenges of large …
A multiscale deep learning approach for high-resolution hyperspectral image classification
Hyperspectral imagery (HSI) has emerged as a highly successful sensing modality for a
variety of applications ranging from urban mapping to environmental monitoring and …
variety of applications ranging from urban mapping to environmental monitoring and …
On combining multiscale deep learning features for the classification of hyperspectral remote sensing imagery
In recent years, satellite imagery has greatly improved in both spatial and spectral
resolution. One of the major unsolved problems in highly developed remote sensing …
resolution. One of the major unsolved problems in highly developed remote sensing …
Deep learning-based classification of hyperspectral data
Classification is one of the most popular topics in hyperspectral remote sensing. In the last
two decades, a huge number of methods were proposed to deal with the hyperspectral data …
two decades, a huge number of methods were proposed to deal with the hyperspectral data …
[HTML][HTML] Deep learning meets hyperspectral image analysis: A multidisciplinary review
Modern hyperspectral imaging systems produce huge datasets potentially conveying a great
abundance of information; such a resource, however, poses many challenges in the …
abundance of information; such a resource, however, poses many challenges in the …
Deep learning for hyperspectral image classification: An overview
Hyperspectral image (HSI) classification has become a hot topic in the field of remote
sensing. In general, the complex characteristics of hyperspectral data make the accurate …
sensing. In general, the complex characteristics of hyperspectral data make the accurate …