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Improved YOLOv4 Based on Attention Mechanism for Ship Detection in SAR Images
2022
IEEE Access
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In order to tackle the above problems, we propose an improved YOLOv4 (ImYOLOv4) based on attention mechanism. ...
Ship detection in synthetic aperture radar (SAR) images is an important and challenging work in the field of image processing. ...
In this paper, we propose a novel one-stage ship detector named improved YOLOv4 (ImYOLOv4) based on attention mechanism [50] for accurate ship detection in SAR images. ...
doi:10.1109/access.2022.3154474
fatcat:6qcuhb3ngrfz3jdtlymey7o5py
Employing deep learning for automatic river bridge detection from SAR images based on Adaptively effective feature fusion
2021
International Journal of Applied Earth Observation and Geoinformation
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Moreover, Gradient Harmonizing Mechanism (GHM) loss function is introduced to solve the problem of sample imbalance in the training process. ...
SSD-AEFF is based on SSD, and AEFF module is innovated to enhance the multi-scale feature maps together with effective Squeeze-Excitation (eSE) module to further fuse effective features and decrease the ...
Gradient Harmonizing Mechanism As an one-stage detector, SSD will produce a large number of candidate boxes during training. ...
doi:10.1016/j.jag.2021.102425
fatcat:4zbbskrqtnh2llwbd7letvdryi
DSDet: A Lightweight Densely Connected Sparsely Activated Detector for Ship Target Detection in High-Resolution SAR Images
2021
Remote Sensing
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Moreover, most state-of-the-art CNN-based ship target detectors that focus on the detection performance ignore the computation complexity. ...
Furthermore, based on the proposed backbone, a low-cost one-stage anchor-free detector is presented. ...
Acknowledgments: We owe many thanks to the authors of HRSID and SSDD for providing the SAR image dataset. ...
doi:10.3390/rs13142743
fatcat:4jdfsuxuljh2zpy6hlesngcx4m
Deep Learning for SAR Ship Detection: Past, Present and Future
2022
Remote Sensing
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Since then, lots of researchers focus their attention on this field. In this paper, we analyze the past, present, and future of the deep learning-based ship detection algorithms in SAR images. ...
In the past section, we analyze the difference between traditional CFAR (constant false alarm rate) based and deep learning-based detectors through theory and experiment. ...
[136] proposed a SAR ship detection method based on a hierarchical attention mechanism. The method includes a global attention module and a local attention module. ...
doi:10.3390/rs14112712
fatcat:dbd6a4ugwjc65pook3wpcuj52a
Target Detection Network for SAR Images Based on Semi-Supervised Learning and Attention Mechanism
2021
Remote Sensing
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Therefore, a SAR target detection network based on a semi-supervised learning and attention mechanism is proposed in this paper. ...
The proposed network consists of a detection branch and a scene recognition branch with a feature extraction module and an attention module shared between these two branches. ...
Conclusions In this paper, a SAR target detection network based on semi-supervised learning and attention mechanism is proposed. ...
doi:10.3390/rs13142686
fatcat:hnegr6edwfgfxfl67s5x4hijzq
Lightweight high-precision SAR ship detection method based on YOLOv7-LDS
2024
PLoS ONE
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This network is founded on Shufflenetv2 and incorporates Squeeze-and-Excitation (SE) attention mechanisms as its key elements. ...
The current challenges in Synthetic Aperture Radar (SAR) ship detection tasks revolve around handling significant variations in target sizes and managing high computational expenses, which hinder practical ...
(a) Ground truth bounding box label map for the targets (b) Without the introduction of an attention mechanism (c) Incorporating the SE attention mechanism (d) Incorporating the CA mechanism (e) Simultaneously ...
doi:10.1371/journal.pone.0296992
pmid:38349872
pmcid:PMC10863868
fatcat:usuyrgc3zjbhvcoenpy4hvvfki
Vehicle Target Detection Network in SAR Images Based on Rectangle-Invariant Rotatable Convolution
2022
Remote Sensing
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Finally, the RIRConv is introduced into the single-shot multibox detector (SSD) to realize SAR vehicle target detection. ...
In recent years, convolutional neural network (CNN)-based methods have been extensively explored for synthetic aperture radar (SAR) target detection. ...
The conventional SAR target detection methods for comparison are two common CFAR detectors, namely, the two-parameters CFAR detector and the Gamma-CFAR detector. ...
doi:10.3390/rs14133086
fatcat:uiveylcu5rgyzcoptbb57m7lta
LS-SSDD-v1.0: A Deep Learning Dataset Dedicated to Small Ship Detection from Large-Scale Sentinel-1 SAR Images
2020
Remote Sensing
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LS-SSDD-v1.0 contains 15 large-scale SAR images whose ground truths are correctly labeled by SAR experts by drawing support from the Automatic Identification System (AIS) and Google Earth. ...
Last but not least, combined with the advantage of abundant pure backgrounds, we also propose a Pure Background Hybrid Training mechanism (PBHT-mechanism) to suppress false alarms of land in large-scale ...
So far, most scholars in this SAR ship detection community still scarcely focus on much information of SAR images and ship identification, when they applied those object detectors in the deep learning ...
doi:10.3390/rs12182997
fatcat:5w7bp7zl5vbpzlab3xsxlfcgwy
A Lightweight Detection Model for SAR Aircraft in a Complex Environment
2021
Remote Sensing
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To alleviate these problems, we propose a lightweight detection model (LDM), mainly including a reuse block (RB) and an information correction block (ICB) based on the Yolov3 framework. ...
Therefore, to accurately extract more aircraft features, we propose an ICB module combining scattering mechanism characteristics by extracting the gray features and enhancing spatial information, which ...
There are many SAR image target detection methods based on attention mechanisms to enhance aircraft features, which mainly employ an attention module, such as CBAM, before the detection part. ...
doi:10.3390/rs13245020
fatcat:mdpbexnvp5fmnarf2g4gpgh2ke
Unsupervised Domain Adaptation for SAR Target Detection
2021
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
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In this work, we proposed an unsupervised Faster R-CNN SAR target detection framework based on domain adaptation, which can improve SAR target detection performance in the unlabeled target domain by borrowing ...
Recent years have witnessed great progress in Synthetic Aperture Radar (SAR) target detection methods based on deep learning. ...
The framework is based on Faster R-CNN target detector and uses VGG16 as the backbone network. ...
doi:10.1109/jstars.2021.3089238
fatcat:ilnvtsix4vhipnm7q4jcfp5bwa
Unboxing the Black Box of Attention Mechanisms in Remote Sensing Big Data Using XAI
2022
Remote Sensing
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This paper presents exploratory work looking into the effectiveness of attention mechanisms (AMs) in improving the task of building segmentation based on convolutional neural network (CNN) backbones. ...
For the XAI portion of this work, the methods of Layer Gradient X activation and Layer DeepLIFT are used to explore the internal AMs and their overall effects on the network. ...
Based on the visualization for DeepLIFT and Gradient, with the deepening of the network, CBAM is able to highlight the building object as the network target and reduces the influences of the background ...
doi:10.3390/rs14246254
fatcat:hj3f5y6urzc77etdr6n5an3rz4
New Horizons in MR Technology: RF Coil Designs and Trends
2007
Magnetic Resonance in Medical Sciences
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To support a large number of detector array coils for parallel imaging, preampliˆers must be physically very small so that they may be tightly packed together to form an optimized detector array. ...
One critical function is to aid in the decoupling of individual coils, which is essential for optimal SNR and the performance of parallel imaging. ...
In this paper, the components of an array coil are explained, and issues requiring special attention are noted. ...
doi:10.2463/mrms.6.29
pmid:17510540
fatcat:aftdohl2pfh3vogvnmaqaiuiyq
A Comprehensive Survey of Machine Learning Applied to Radar Signal Processing
[article]
2020
arXiv
pre-print
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The main applications of ML-based RSP are then analysed and structured based on the application field. ...
Modern radar systems have high requirements in terms of accuracy, robustness and real-time capability when operating on increasingly complex electromagnetic environments. ...
This model also used attention mechanism to rule out false alarms in complex scenarios. ...
arXiv:2009.13702v1
fatcat:m6am73324zdwba736sn3vmph3i
2021 Index IEEE/ACM Transactions on Audio, Speech, and Language Processing Vol. 29
2021
IEEE/ACM Transactions on Audio Speech and Language Processing
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The primary entry includes the coauthors' names, the title of the paper or other item, and its location, specified by the publication abbreviation, year, and inclusive pagination. ...
-that appeared in this periodical during 2021, and items from previous years that were commented upon or corrected in 2021. ...
Detection of Multiple Steganography Methods in Compressed Speech Based on Code Element Embedding, Bi-LSTM and CNN With Attention Mechanisms. ...
doi:10.1109/taslp.2022.3147096
fatcat:7nl52k7sjfalbhpxtum3y5nmje
2021 Index IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing Vol. 14
2021
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
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The primary entry includes the coauthors' names, the title of the paper or other item, and its location, specified by the publication abbreviation, year, month, and inclusive pagination. ...
The Subject Index contains entries describing the item under all appropriate subject headings, plus the first author's name, the publication abbreviation, month, and year, and inclusive pages. ...
., +, JSTARS 2021 3967-3987 A Novel CNN-Based Detector for Ship Detection Based on Rotatable Bounding Box in SAR Images. ...
doi:10.1109/jstars.2022.3143012
fatcat:dnetkulbyvdyne7zxlblmek2qy
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