Automatic target recognition in synthetic aperture radar imagery: A state-of-the-art review
The purpose of this paper is to survey and assess the state-of-the-art in automatic target
recognition for synthetic aperture radar imagery (SAR-ATR). The aim is not to develop an …
recognition for synthetic aperture radar imagery (SAR-ATR). The aim is not to develop an …
Development and application of ship detection and classification datasets: A review
C Zhang, X Zhang, G Gao, H Lang, G Liu… - … and Remote Sensing …, 2024 - ieeexplore.ieee.org
Ship detection and classification pose significant challenges in remote sensing. The potent
feature extraction capabilities of deep learning algorithms render them pivotal for these …
feature extraction capabilities of deep learning algorithms render them pivotal for these …
HOG-ShipCLSNet: A novel deep learning network with hog feature fusion for SAR ship classification
Ship classification in synthetic aperture radar (SAR) images is a fundamental and significant
step in ocean surveillance. Recently, with the rise of deep learning (DL), modern abstract …
step in ocean surveillance. Recently, with the rise of deep learning (DL), modern abstract …
A polarization fusion network with geometric feature embedding for SAR ship classification
T Zhang, X Zhang - Pattern Recognition, 2022 - Elsevier
Current synthetic aperture radar (SAR) ship classifiers using convolutional neural networks
(CNNs) offer state-of-the-art performance. Yet, they still have two defects potentially …
(CNNs) offer state-of-the-art performance. Yet, they still have two defects potentially …
OpenSARShip: A dataset dedicated to Sentinel-1 ship interpretation
With the rapid growth of Sentinel-1 synthetic aperture radar (SAR) data, how to exploit
Sentinel-1 imagery and achieve effective and robust marine surveillance are crucial …
Sentinel-1 imagery and achieve effective and robust marine surveillance are crucial …
Squeeze-and-excitation Laplacian pyramid network with dual-polarization feature fusion for ship classification in SAR images
T Zhang, X Zhang - IEEE Geoscience and Remote Sensing …, 2021 - ieeexplore.ieee.org
This letter proposes a squeeze-and-excitation Laplacian pyramid network with dual-
polarization feature fusion (SE-LPN-DPFF) for ship classification in synthetic aperture radar …
polarization feature fusion (SE-LPN-DPFF) for ship classification in synthetic aperture radar …
A bilateral CFAR algorithm for ship detection in SAR images
X Leng, K Ji, K Yang, H Zou - IEEE Geoscience and Remote …, 2015 - ieeexplore.ieee.org
A bilateral constant false alarm rate (CFAR) algorithm for ship detection in synthetic aperture
radar (SAR) images is proposed in this letter. Compared to the standard CFAR algorithm …
radar (SAR) images is proposed in this letter. Compared to the standard CFAR algorithm …
Discriminant deep belief network for high-resolution SAR image classification
Classification plays an important role in many fields of synthetic aperture radar (SAR) image
understanding and interpretation. Many scholars have devoted to design features to …
understanding and interpretation. Many scholars have devoted to design features to …
Ship classification in high-resolution SAR images using deep learning of small datasets
Y Wang, C Wang, H Zhang - Sensors, 2018 - mdpi.com
With the capability to automatically learn discriminative features, deep learning has
experienced great success in natural images but has rarely been explored for ship …
experienced great success in natural images but has rarely been explored for ship …
Injection of traditional hand-crafted features into modern CNN-based models for SAR ship classification: What, why, where, and how
T Zhang, X Zhang - Remote Sensing, 2021 - mdpi.com
With the rise of artificial intelligence, many advanced Synthetic Aperture Radar (SAR) ship
classifiers based on convolutional neural networks (CNNs) have achieved better accuracies …
classifiers based on convolutional neural networks (CNNs) have achieved better accuracies …