Using artificial intelligence and data fusion for environmental monitoring: A review and future perspectives
Analyzing satellite images and remote sensing (RS) data using artificial intelligence (AI)
tools and data fusion strategies has recently opened new perspectives for environmental …
tools and data fusion strategies has recently opened new perspectives for environmental …
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 …
Rotation-invariant attention network for hyperspectral image classification
Hyperspectral image (HSI) classification refers to identifying land-cover categories of pixels
based on spectral signatures and spatial information of HSIs. In recent deep learning-based …
based on spectral signatures and spatial information of HSIs. In recent deep learning-based …
Novel adaptive region spectral–spatial features for land cover classification with high spatial resolution remotely sensed imagery
Spectral–spatial features are important for ground target identification and classification with
high spatial resolution remotely sensed (HSRRS) Imagery. In this article, two novel features …
high spatial resolution remotely sensed (HSRRS) Imagery. In this article, two novel features …
A cross Transformer for image denoising
Deep convolutional neural networks (CNNs) depend on feedforward and feedback ways to
obtain good performance in image denoising. However, how to obtain effective structural …
obtain good performance in image denoising. However, how to obtain effective structural …
A semisupervised Siamese network for hyperspectral image classification
With the development of hyperspectral imaging technology, hyperspectral images (HSIs)
have become important when analyzing the class of ground objects. In recent years …
have become important when analyzing the class of ground objects. In recent years …
[HTML][HTML] Information fusion and artificial intelligence for smart healthcare: a bibliometric study
With the fast progress in information technologies and artificial intelligence (AI), smart
healthcare has gained considerable momentum. By using advanced technologies like AI …
healthcare has gained considerable momentum. By using advanced technologies like AI …
Coupled adversarial learning for fusion classification of hyperspectral and LiDAR data
Hyperspectral image (HSI) provides rich spectral–spatial information and the light detection
and ranging (LiDAR) data reflect the elevation information, which can be jointly exploited for …
and ranging (LiDAR) data reflect the elevation information, which can be jointly exploited for …
Big data and machine learning with hyperspectral information in agriculture
KLM Ang, JKP Seng - IEEE Access, 2021 - ieeexplore.ieee.org
Hyperspectral and multispectral information processing systems and technologies have
demonstrated its usefulness for the improvement of agricultural productivity and practices by …
demonstrated its usefulness for the improvement of agricultural productivity and practices by …
A novel hyperspectral image classification model using bole convolution with three-direction attention mechanism: small sample and unbalanced learning
Currently, the use of rich spectral and spatial information of hyperspectral images (HSIs) to
classify ground objects is a research hotspot. However, the classification ability of existing …
classify ground objects is a research hotspot. However, the classification ability of existing …