Object detection and image segmentation with deep learning on Earth observation data: A review—Part II: Applications
In Earth observation (EO), large-scale land-surface dynamics are traditionally analyzed by
investigating aggregated classes. The increase in data with a very high spatial resolution …
investigating aggregated classes. The increase in data with a very high spatial resolution …
A survey on the applications of convolutional neural networks for synthetic aperture radar: Recent advances
In recent years, convolutional neural networks (CNNs) have drawn considerable attention
for the analysis of synthetic aperture radar (SAR) data. In this study, major subareas of SAR …
for the analysis of synthetic aperture radar (SAR) data. In this study, major subareas of SAR …
Mapping irrigated areas using Sentinel-1 time series in Catalonia, Spain
Mapping irrigated plots is essential for better water resource management. Today, the free
and open access Sentinel-1 (S1) and Sentinel-2 (S2) data with high revisit time offers a …
and open access Sentinel-1 (S1) and Sentinel-2 (S2) data with high revisit time offers a …
Enhanced bearing fault detection using multichannel, multilevel 1D CNN classifier
Electric motors are widely used in many industrial applications on account of stability,
solidity and ease of use. Mechanical bearing faults have the highest statistical occurrence …
solidity and ease of use. Mechanical bearing faults have the highest statistical occurrence …
A comprehensive survey of machine learning applied to radar signal processing
P Lang, X Fu, M Martorella, J Dong, R Qin… - arXiv preprint arXiv …, 2020 - arxiv.org
Modern radar systems have high requirements in terms of accuracy, robustness and real-
time capability when operating on increasingly complex electromagnetic environments …
time capability when operating on increasingly complex electromagnetic environments …
Wide-area land cover mapping with Sentinel-1 imagery using deep learning semantic segmentation models
S Šćepanović, O Antropov, P Laurila… - IEEE Journal of …, 2021 - ieeexplore.ieee.org
Land cover (LC) mapping is essential for monitoring the environment and understanding the
effects of human activities on it. Recent studies demonstrated successful applications of …
effects of human activities on it. Recent studies demonstrated successful applications of …
Environment monitoring of Shanghai Nanhui intertidal zone with dual-polarimetric SAR data based on deep learning
Satellite-based synthetic aperture radar (SAR) can provide low-cost, frequent environment
monitoring for dynamic intertidal zones. The critical problem is to realize pixel-level …
monitoring for dynamic intertidal zones. The critical problem is to realize pixel-level …
[HTML][HTML] Utilizing a single-temporal full polarimetric Gaofen-3 SAR image to map coseismic landslide inventory following the 2017 Mw 7.0 Jiuzhaigou earthquake …
Abstract On August 8, 2017, a magnitude 7.0 earthquake struck Jiuzhaigou County in
Sichuan Province, triggering numerous coseismic landslides. The prompt identification of …
Sichuan Province, triggering numerous coseismic landslides. The prompt identification of …
Stress detection using ppg signal and combined deep cnn-mlp network
Y Hasanpoor, K Motaman… - 2022 29th National …, 2022 - ieeexplore.ieee.org
Stress has become a fact in people's lives. It has a significant effect on the function of body
systems and many key systems of the body including respiratory, cardiovascular, and even …
systems and many key systems of the body including respiratory, cardiovascular, and even …
Classification of polarimetric SAR images using compact convolutional neural networks
Classification of polarimetric synthetic aperture radar (PolSAR) images is an active research
area with a major role in environmental applications. The traditional Machine Learning (ML) …
area with a major role in environmental applications. The traditional Machine Learning (ML) …