Semisupervised SAR ship detection network via scene characteristic learning
In recent years, target detection methods based on deep learning have achieved extensive
development in synthetic aperture radar (SAR) ship detection. However, training such …
development in synthetic aperture radar (SAR) ship detection. However, training such …
Regional prediction-aware network with cross-scale self-attention for ship detection in SAR images
L Zhang, Y Liu, Y Huang, L Qu - IEEE Geoscience and Remote …, 2022 - ieeexplore.ieee.org
Deep learning algorithms have been widely used in ship detection with synthetic aperture
radar (SAR). However, the complex background, clutter noise, and large span of ship sizes …
radar (SAR). However, the complex background, clutter noise, and large span of ship sizes …
FINet: A feature interaction network for SAR ship object-level and pixel-level detection
Deep learning-based detection methods have achieved great success in ship target
detection in synthetic aperture radar (SAR) images. However, due to the interference of …
detection in synthetic aperture radar (SAR) images. However, due to the interference of …
A lightweight SAR ship detector using end-to-end image preprocessing network and channel feature guided spatial pyramid pooling
Recently, in the field of synthetic aperture radar (SAR) ship detection, deep-learning-based
methods have made significant strides in terms of detection accuracy and speed. However …
methods have made significant strides in terms of detection accuracy and speed. However …
Multiscale and dense ship detection in SAR images based on key-point estimation and attention mechanism
Ship target detection in synthetic aperture radar (SAR) images is essential for many
applications in marine monitoring and port security. Though considerable developments …
applications in marine monitoring and port security. Though considerable developments …
Enhanced feature extraction for ship detection from multi-resolution and multi-scene synthetic aperture radar (SAR) images
Independent of daylight and weather conditions, synthetic aperture radar (SAR) images
have been widely used for ship monitoring. The traditional methods for SAR ship detection …
have been widely used for ship monitoring. The traditional methods for SAR ship detection …
Unsupervised domain-adaptive sar ship detection based on cross-domain feature interaction and data contribution balance
Y Yang, J Chen, L Sun, Z Zhou, Z Huang, B Wu - Remote Sensing, 2024 - mdpi.com
Due to the complex imaging mechanism of SAR images and the lack of multi-angle and
multi-parameter real scene SAR target data, the generalization performance of existing deep …
multi-parameter real scene SAR target data, the generalization performance of existing deep …
CroMoDa: Unsupervised Oriented SAR Ship Detection via Cross-Modality Distribution Alignment
Most state-of-the-art synthetic aperture radar (SAR) ship detection methods based on deep
learning require large amounts of labeled data for network training. However, the annotation …
learning require large amounts of labeled data for network training. However, the annotation …
A Spatial Cross-Scale Attention Network and Global Average Accuracy Loss for SAR Ship Detection
L Zhang, Y Liu, L Qu, J Cai, J Fang - Remote Sensing, 2023 - mdpi.com
A neural network-based object detection algorithm has the advantages of high accuracy and
end-to-end processing, and it has been widely used in synthetic aperture radar (SAR) ship …
end-to-end processing, and it has been widely used in synthetic aperture radar (SAR) ship …
Contextual region-based convolutional neural network with multilayer fusion for SAR ship detection
M Kang, K Ji, X Leng, Z Lin - Remote Sensing, 2017 - mdpi.com
Synthetic aperture radar (SAR) ship detection has been playing an increasingly essential
role in marine monitoring in recent years. The lack of detailed information about ships in …
role in marine monitoring in recent years. The lack of detailed information about ships in …