An anchor-free method based on feature balancing and refinement network for multiscale ship detection in SAR images

J Fu, X Sun, Z Wang, K Fu - IEEE Transactions on Geoscience …, 2020 - ieeexplore.ieee.org
Recently, deep-learning methods have been successfully applied to the ship detection in the
synthetic aperture radar (SAR) images. It is still a great challenge to detect multiscale SAR …

BANet: A balance attention network for anchor-free ship detection in SAR images

Q Hu, S Hu, S Liu - IEEE Transactions on Geoscience and …, 2022 - ieeexplore.ieee.org
Recently, methods based on deep learning have been successfully applied to ship detection
for synthetic aperture radar (SAR) images. However, most current ship detection networks …

A densely connected end-to-end neural network for multiscale and multiscene SAR ship detection

J Jiao, Y Zhang, H Sun, X Yang, X Gao, W Hong… - Ieee …, 2018 - ieeexplore.ieee.org
Synthetic aperture radar (SAR) images have been widely used for ship monitoring. The
traditional methods of SAR ship detection are difficult to detect small scale ships and avoid …

A fast and lightweight detection network for multi-scale SAR ship detection under complex backgrounds

J Yu, G Zhou, S Zhou, M Qin - Remote Sensing, 2021 - mdpi.com
It is very difficult to detect multi-scale synthetic aperture radar (SAR) ships, especially under
complex backgrounds. Traditional constant false alarm rate methods are cumbersome in …

A novel detector based on convolution neural networks for multiscale SAR ship detection in complex background

W Dai, Y Mao, R Yuan, Y Liu, X Pu, C Li - Sensors, 2020 - mdpi.com
Convolution neural network (CNN)-based detectors have shown great performance on ship
detections of synthetic aperture radar (SAR) images. However, the performance of current …

Anchor-free convolutional network with dense attention feature aggregation for ship detection in SAR images

F Gao, Y He, J Wang, A Hussain, H Zhou - Remote Sensing, 2020 - mdpi.com
In recent years, with the improvement of synthetic aperture radar (SAR) imaging resolution, it
is urgent to develop methods with higher accuracy and faster speed for ship detection in …

A robust one-stage detector for multiscale ship detection with complex background in massive SAR images

X Yang, X Zhang, N Wang, X Gao - IEEE Transactions on …, 2021 - ieeexplore.ieee.org
With the development of synthetic aperture radar (SAR) imaging and deep learning, SAR
ship detection based on convolutional neural networks (CNNs) has been extensively …

Feature enhancement pyramid and shallow feature reconstruction network for SAR ship detection

L Bai, C Yao, Z Ye, D Xue, X Lin… - IEEE Journal of Selected …, 2023 - ieeexplore.ieee.org
Recently, convolutional neural network based methods have been studied for ship detection
in optical remote sensing images. However, it is challenging to apply them to microwave …

MSARN: A deep neural network based on an adaptive recalibration mechanism for multiscale and arbitrary-oriented SAR ship detection

C Chen, C He, C Hu, H Pei, L Jiao - IEEE Access, 2019 - ieeexplore.ieee.org
Ship detection plays an important role in synthetic aperture radar (SAR) image
interpretation. However, there are still some difficulties in SAR ship detection. First, ships …

A deep neural network based on an attention mechanism for SAR ship detection in multiscale and complex scenarios

C Chen, C He, C Hu, H Pei, L Jiao - Ieee Access, 2019 - ieeexplore.ieee.org
Synthetic aperture radar (SAR) ship detection based on deep learning has been widely
applied in recent years. However, two main obstacles are hindering SAR ship detection …