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Towards a Reliable and Sensitive Deep Learning Based Approach for Multi-Ship Detection in SAR Imagery
2021
International Journal of Geoinformatics
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In this paper, a three-step ship detection process is described and a reliable and sensitive hybrid deep learning model is proposed as an efficient classifier in the middle step. ...
Recently, Deep learning-based object detection techniques have impressive results in most detection applications but unfortunately there are challenging problems such as difficulty of detecting multiple ...
In this paper, a hybrid Deep Learning (DL) approach, based on Convolution Neural Network (CNN) model and Long Short Term Memory (LSTM) model, is presented as a reliable and sensitive classifier to enhance ...
doi:10.52939/ijg.v17i6.2067
fatcat:ulgiphrf6rf7jorq6j6gazefbi
Deep Learning for SAR Ship Detection: Past, Present and Future
2022
Remote Sensing
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As a result, it is also used to detect ships in SAR images. ...
After the revival of deep learning in computer vision in 2012, SAR ship detection comes into the deep learning era too. ...
Therefore, in recent years, deep learning-based SAR ship detection algorithms have become a new research hotspot. ...
doi:10.3390/rs14112712
fatcat:dbd6a4ugwjc65pook3wpcuj52a
The QXS-SAROPT Dataset for Deep Learning in SAR-Optical Data Fusion
[article]
2021
arXiv
pre-print
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Here, we present a detailed introduction of the construction of the dataset, and show its two representative exemplary applications, namely SAR-optical image matching and SAR ship detection boosted by ...
As a large open SAR-optical dataset with multiple scenes of a high resolution, we believe QXS-SAROPT will be of potential value for further research in SAR-optical data fusion technology based on deep ...
SAR ship detection SAR ship detection in complex scenes is a great challenging task. ...
arXiv:2103.08259v2
fatcat:fbiewxxluncb5bwg5p6q3r6ywu
Ship Velocity Estimation From Ship Wakes Detected Using Convolutional Neural Networks
2019
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
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Consequently, we propose a method whereby a CNN is applied to automatically detect ship wakes from TanDEM-X data. ...
Here, we investigated the potential for automatic estimation of ship velocity using the azimuth offset between ships and wakes detected using convolutional neural network (CNN) coupled with SAR imagery ...
By utilizing deep learning for wake detection, ship velocity can be estimated from a single SAR image based on the azimuth offset between ships and wakes. ...
doi:10.1109/jstars.2019.2949006
fatcat:thqhwdc2ljagxdkkqyfr732ldq
Study on the Combined Application of CFAR and Deep Learning in Ship Detection
2018
Journal of the Indian Society of Remote Sensing
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detection can be improved by analysing big data, such as by deep learning. ...
Thus, a ship detection algorithm that combines CFAR and CNN is proposed based on the CFAR global detection algorithm and image recognition with the CNN model. ...
creative commons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a ...
doi:10.1007/s12524-018-0787-x
fatcat:k5jpbwhrgbgwvfffpl33ny6j64
A Bridge Neural Network-Based Optical-SAR Image Joint Intelligent Interpretation Framework
2021
Space Science & Technology
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In particular, based on the QXS-SAROPT dataset, our framework can achieve up to 96% high accuracy on four benchmark SAR ship detection datasets. ...
To solve this problem, we propose a bridge neural network- (BNN-) based optical-SAR image joint intelligent interpretation framework, optimizing the feature correlation between optical and SAR images through ...
Introduction With the rapid development of deep learning, remarkable breakthroughs have been made in deep learning-based land use segmentation, scene classification, object detection, and recognition in ...
doi:10.34133/2021/9841456
fatcat:6sbaoa75vvgpxgfie6f6jrrk64
A Computational Framework for Iceberg and Ship Discrimination: Case Study on Kaggle Competition
2020
IEEE Access
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This study presents a computational framework for iceberg and ship discrimination based on an ensemble of various deep learning and machine learning algorithms. ...
Here, the identification aims to detect ocean SAR targets and then categorize these targets into iceberg, ship, or unknown. ...
These ship detection algorithms were applied for the detection of icebergs from SAR data. One of the simple but widely used methods is the threshold-based detection algorithm. ...
doi:10.1109/access.2020.2990985
fatcat:krf4mrs6vfgpjariduurl5semq
Multi-Scale Ship Detection from SAR and Optical Imagery via A More Accurate YOLOv3
2021
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
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Index Terms-Ship detection, deep learning-based object detection, YOLOv3, SAR and optical imagery. S This work is licensed under a Creative Commons Attribution 4.0 License. ...
Deep learning detection methods use in ship detection remains a challenge, owing to the small scale of the objects and interference from complex sea surfaces. ...
However, deep learning based on object detection tends to underperform when applied to remote sensing image-based ship detection. ...
doi:10.1109/jstars.2021.3087555
fatcat:6xsn6bzqt5dhjimzq5crgxbbze
SAR Ship Detection Dataset (SSDD): Official Release and Comprehensive Data Analysis
2021
Remote Sensing
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SAR Ship Detection Dataset (SSDD) is the first open dataset that is widely used to research state-of-the-art technology of ship detection from synthetic aperture radar (SAR) imagery based on deep learning ...
According to our investigation, up to 46.59% of the total 161 public reports confidently select SSDD to study DL-based SAR ship detection. ...
learning based on improved SSD Symmetry 2021-03-23 Chen et al. [90] End-to-end ship detection in SAR images for complex scenes based on deep CNNs Journal of Sensors 64 2021-03-24 He et al. [91] Learning ...
doi:10.3390/rs13183690
fatcat:eo2vjj6majaenjna6ilq3tpdam
Ship Detection from X-Band SAR Images Using M2Det Deep Learning Model
2020
Applied Sciences
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The results of this study are expected to contribute to the development of deep learning-based ship detection techniques in SAR images in the future. ...
In recent years, the development of deep learning techniques has facilitated studies on ship detection in SAR images using deep learning techniques. ...
Figure 3 shows a flow chart of the SAR image preprocessing performed to improve the ship detection performance using deep learning. ...
doi:10.3390/app10217751
fatcat:z6k6ptxkyfbqxcirwx4bg225ea
Visualization of Deep Transfer Learning In SAR Imagery
[article]
2021
arXiv
pre-print
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2020
IGARSS 2020 - 2020 IEEE International Geoscience and Remote Sensing Symposium
unpublished
doi:10.1109/igarss39084.2020.9324490 fatcat:smhjikfoqvddrpfvfs43jiusfi
doi:10.1109/igarss39084.2020.9324490 fatcat:smhjikfoqvddrpfvfs43jiusfi
In this work, we consider transfer learning to leverage deep features from a network trained on an EO ships dataset and generate predictions on SAR imagery. ...
Furthermore, by exploring the network activations in the form of class-activation maps (CAMs), we visualize the transfer learning process to SAR imagery and gain insight on how a deep network interprets ...
In this paper, we utilize EO data for pretraining a deep network and then perform transfer learning with SAR data to the new domain. ...
arXiv:2103.11061v1
fatcat:lv5v5lrg4fdbrpcpjtgs2iwcvu
Deep Learning Meets SAR
[article]
2021
arXiv
pre-print
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2020 pre-print arXiv:2006.10027v1 fatcat:sjdqhdimfjdufazmwihs7zftku
of deep learning applied to SAR in depth, summarize available benchmarks, and recommend some important future research directions. ...
Although deep learning has been introduced in Synthetic Aperture Radar (SAR) data processing, despite successful first attempts, its huge potential remains locked. ...
As first attempts in SAR, deep learning-based methods have been adopted for a variety of tasks, including terrain surface classification [6] , object detection [7] , parameter inversion [8] , despeckling ...
arXiv:2006.10027v2
fatcat:s3tiroz4qve6nbhavtz77fbis4
An improved anchor-free SAR ship detection algorithm based on brain-inspired attention mechanism
2022
Frontiers in Neuroscience
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Secondly, in order to improve the SAR ship target feature extraction capability, a dense connection module is proposed for the deep part of the network to promote more adequate deep feature fusion. ...
Therefore, this paper proposes an improved anchor-free SAR ship detection algorithm based on brain-inspired attention mechanism, which efficiently focuses on target information ignoring the interference ...
regression tasks, and target detection using deep learning has now become mainstream. ...
doi:10.3389/fnins.2022.1074706
pmid:36532272
pmcid:PMC9748563
fatcat:gp5bbeyku5f2hkdkrqzqeagm44
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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However, today, there is still a lack of a reliable deep learning SAR ship detection dataset that can meet the practical migration application of ship detection in large-scene space-borne SAR images. ...
In recent years, as the rise of artificial intelligence, deep learning has almost dominated SAR ship detection community for its higher accuracy, faster speed, less human intervention, etc. ...
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
Deep Neural Network Based Detection and Segmentation of Ships for Maritime Surveillance
2023
Computer systems science and engineering
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This paper proposes a deep learning based model capable enough to classify between ships and noships as well as to localize ships in the original images using bounding box technique. ...
Furthermore, classified ships are again segmented with deep learning based auto-encoder model. ...
In [15] , an enhanced GPU based deep learning method for ship detection using SAR images is reported. ...
doi:10.32604/csse.2023.024997
fatcat:prqcgnyrhjbzhcyqd3bgpyza7u
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