Deep supervised and contractive neural network for SAR image classification
The classification of a synthetic aperture radar (SAR) image is a significant yet challenging
task, due to the presence of speckle noises and the absence of effective feature …
task, due to the presence of speckle noises and the absence of effective feature …
A two-phase algorithm based on kurtosis curvelet energy and unsupervised spectral regression for segmentation of SAR images
Z Tirandaz, G Akbarizadeh - IEEE journal of selected topics in …, 2015 - ieeexplore.ieee.org
Texture-based segmentation of synthetic aperture radar (SAR) image is a difficult task in
remote sensing applications because it must address the problem of speckle noise. Several …
remote sensing applications because it must address the problem of speckle noise. Several …
Unsupervised single-scene semantic segmentation for earth observation
Earth observation data have huge potential to enrich our knowledge about our planet. An
important step in many Earth observation tasks is semantic segmentation. Generally, a large …
important step in many Earth observation tasks is semantic segmentation. Generally, a large …
Global intuitionistic fuzzy weighted C-ordered means clustering algorithm
The paper proposes a novel approach to address the challenges of clustering datasets and
identifying outliers by utilizing the Atanassov intuitionistic fuzzy sets (AIFS) environment. The …
identifying outliers by utilizing the Atanassov intuitionistic fuzzy sets (AIFS) environment. The …
[HTML][HTML] Feature merged network for oil spill detection using SAR images
The frequency of marine oil spills has increased in recent years. The growing exploitation of
marine oil and continuous increase in marine crude oil transportation has caused …
marine oil and continuous increase in marine crude oil transportation has caused …
SAR image segmentation based on constrained smoothing and hierarchical label correction
Synthetic aperture radar (SAR) is widely used in the field of modern remote sensing due to
its high resolution for a comparatively small antenna. However, there are still some …
its high resolution for a comparatively small antenna. However, there are still some …
Automatic land cover classification of multi-resolution dualpol data using convolutional neural network (CNN)
Abstract Synthetic Aperture Radar is an interesting topic of research for scientists &
researchers as it is associated with polarimetric information which helps to detect surface & …
researchers as it is associated with polarimetric information which helps to detect surface & …
Online regulation of high speed train trajectory control based on TS fuzzy bilinear model
H Yang, KP Zhang, HE Liu - IEEE Transactions on Intelligent …, 2015 - ieeexplore.ieee.org
Multiobjective operation optimization for high-speed trains (HSTs) is hardly implemented by
manual operation due to the increasing operational complexity and environmental …
manual operation due to the increasing operational complexity and environmental …
[HTML][HTML] Dialectical GAN for SAR image translation: From Sentinel-1 to TerraSAR-X
With more and more SAR applications, the demand for enhanced high-quality SAR images
has increased considerably. However, high-quality SAR images entail high costs, due to the …
has increased considerably. However, high-quality SAR images entail high costs, due to the …
Covariance of textural features: A new feature descriptor for SAR image classification
Synthetic aperture radar (SAR) image land-cover classification is an important research
topic in SAR image interpretation. However, speckle, inherent of active coherent imaging …
topic in SAR image interpretation. However, speckle, inherent of active coherent imaging …