Transfer learning in environmental remote sensing
Abstract Machine learning (ML) has proven to be a powerful tool for utilizing the rapidly
increasing amounts of remote sensing data for environmental monitoring. Yet ML models …
increasing amounts of remote sensing data for environmental monitoring. Yet ML models …
[HTML][HTML] Review of image classification algorithms based on convolutional neural networks
Image classification has always been a hot research direction in the world, and the
emergence of deep learning has promoted the development of this field. Convolutional …
emergence of deep learning has promoted the development of this field. Convolutional …
[HTML][HTML] Deep learning-based change detection in remote sensing images: A review
Images gathered from different satellites are vastly available these days due to the fast
development of remote sensing (RS) technology. These images significantly enhance the …
development of remote sensing (RS) technology. These images significantly enhance the …
A deeply supervised attention metric-based network and an open aerial image dataset for remote sensing change detection
Change detection (CD) aims to identify surface changes from bitemporal images. In recent
years, deep learning (DL)-based methods have made substantial breakthroughs in the field …
years, deep learning (DL)-based methods have made substantial breakthroughs in the field …
Land use and land cover classification with hyperspectral data: A comprehensive review of methods, challenges and future directions
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 geological hazards analysis: Data, models, applications, and opportunities
As natural disasters are induced by geodynamic activities or abnormal changes in the
environment, geological hazards tend to wreak havoc on the environment and human …
environment, geological hazards tend to wreak havoc on the environment and human …
Vision transformers for remote sensing image classification
In this paper, we propose a remote-sensing scene-classification method based on vision
transformers. These types of networks, which are now recognized as state-of-the-art models …
transformers. These types of networks, which are now recognized as state-of-the-art models …
Remote sensing image scene classification meets deep learning: Challenges, methods, benchmarks, and opportunities
Remote sensing image scene classification, which aims at labeling remote sensing images
with a set of semantic categories based on their contents, has broad applications in a range …
with a set of semantic categories based on their contents, has broad applications in a range …
[HTML][HTML] Deep learning in remote sensing applications: A meta-analysis and review
Deep learning (DL) algorithms have seen a massive rise in popularity for remote-sensing
image analysis over the past few years. In this study, the major DL concepts pertinent to …
image analysis over the past few years. In this study, the major DL concepts pertinent to …
Building extraction with vision transformer
As an important carrier of human productive activities, the extraction of buildings is not only
essential for urban dynamic monitoring but also necessary for suburban construction …
essential for urban dynamic monitoring but also necessary for suburban construction …