[HTML][HTML] Change detection based on artificial intelligence: State-of-the-art and challenges
Change detection based on remote sensing (RS) data is an important method of detecting
changes on the Earth's surface and has a wide range of applications in urban planning …
changes on the Earth's surface and has a wide range of applications in urban planning …
Deep learning for change detection in remote sensing: a review
ABSTRACT A large number of publications have incorporated deep learning in the process
of remote sensing change detection. In these Deep Learning Change Detection (DLCD) …
of remote sensing change detection. In these Deep Learning Change Detection (DLCD) …
[HTML][HTML] End-to-end change detection for high resolution satellite images using improved UNet++
Change detection (CD) is essential to the accurate understanding of land surface changes
using available Earth observation data. Due to the great advantages in deep feature …
using available Earth observation data. Due to the great advantages in deep feature …
[HTML][HTML] Change detection of deforestation in the Brazilian Amazon using landsat data and convolutional neural networks
PP De Bem, OA de Carvalho Junior… - Remote Sensing, 2020 - mdpi.com
Mapping deforestation is an essential step in the process of managing tropical rainforests. It
lets us understand and monitor both legal and illegal deforestation and its implications …
lets us understand and monitor both legal and illegal deforestation and its implications …
[HTML][HTML] Double-branch multi-attention mechanism network for hyperspectral image classification
Recently, Hyperspectral Image (HSI) classification has gradually been getting attention from
more and more researchers. HSI has abundant spectral and spatial information; thus, how to …
more and more researchers. HSI has abundant spectral and spatial information; thus, how to …
Analysis on change detection techniques for remote sensing applications: A review
Satellite images taken on the earth's surface are analyzed to identify the spatial and
temporal changes that have occurred naturally or manmade. Real-time prediction of change …
temporal changes that have occurred naturally or manmade. Real-time prediction of change …
From W-Net to CDGAN: Bitemporal change detection via deep learning techniques
Traditional change detection methods usually follow the image differencing, change feature
extraction, and classification framework, and their performance is limited by such simple …
extraction, and classification framework, and their performance is limited by such simple …
Cross-attention guided group aggregation network for cropland change detection
Cropland resources are essential for the provision of food production, which is one of the
most fundamental needs of human life. Change detection (CD) technology enables the …
most fundamental needs of human life. Change detection (CD) technology enables the …
[HTML][HTML] Spatiotemporal mapping and monitoring of mangrove forests changes from 1990 to 2019 in the Northern Emirates, UAE using random forest, Kernel logistic …
Mangrove forests are acting as a green lung for the coastal cities of the United Arab
Emirates, providing a habitat for wildlife, storing blue carbon in sediment and protecting …
Emirates, providing a habitat for wildlife, storing blue carbon in sediment and protecting …
Capsule networks for image classification: A review
Over the past few years, the computer vision domain has evolved and made a revolutionary
transition from human-engineered features to automated features to address challenging …
transition from human-engineered features to automated features to address challenging …