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Deep learning applied to underwater mine warfare

https://doi.org/10.1109/oceanse.2017.8084910
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What this work says

Outgoing claims: the papers this work cites, builds on, or argues with.

inferredcites →https://doi.org/10.1007/bf00332918openalex-snapshot
Auto-association by multilayer perceptrons and singular value decomposition
inferredcites →https://doi.org/10.1016/j.cviu.2014.12.006openalex-snapshot
On rendering synthetic images for training an object detector
inferredcites →https://doi.org/10.1109/oceanse.2005.1513166openalex-snapshot
Automatic classification for MCM systems
inferredcites →https://doi.org/10.1145/1390156.1390294openalex-snapshot
Extracting and composing robust features with denoising autoencoders
inferredcites →https://doi.org/10.23919/oceans.2013.6741048openalex-snapshot
Development of image sonar simulator for underwater object recognition
inferredcites →https://doi.org/10.48550/arxiv.1409.1556openalex-snapshot
Very Deep Convolutional Networks for Large-Scale Image Recognition
inferredcites →https://doi.org/10.5772/39406openalex-snapshot
Simulation and 3D Reconstruction of Side-Looking Sonar Images

What points at this work

Incoming claims: where this work appears in other papers’ reference lists and arguments.

inferred← citeshttps://doi.org/10.2139/ssrn.4678942openalex-extracted
inferred← citeshttps://doi.org/10.1007/978-3-031-87154-2_58openalex-snapshot
Automatic Mine Detection for Underwater and Surface Vehicles
inferred← citeshttps://doi.org/10.1007/978-981-16-2937-2_20openalex-snapshot
Data Processing and Analytics for National Security Intelligence: An Overview
inferred← citeshttps://doi.org/10.1007/978-981-96-4145-1_20openalex-snapshot
Bridging Traditional Techniques and AI-Driven Approaches in Image Deconvolution: From Classical Approach to Cutting Edge Techniques
inferred← citeshttps://doi.org/10.1007/s11042-020-09221-wopenalex-snapshot
Saliency-based classification of objects in unconstrained underwater environments
inferred← citeshttps://doi.org/10.1007/s11042-023-16757-0openalex-snapshot
An imaging algorithm for high-resolution imaging sonar system
inferred← citeshttps://doi.org/10.1016/j.future.2021.07.011openalex-snapshot
Object detection/tracking toward underwater photographs by remotely operated vehicles (ROVs)
inferred← citeshttps://doi.org/10.1016/j.ifacol.2019.12.299openalex-snapshot
Deep Learning based Object Detection via Style-transferred Underwater Sonar Images
inferred← citeshttps://doi.org/10.1016/j.ifacol.2019.12.322openalex-snapshot
Realistic Sonar Image Simulation Using Generative Adversarial Network
inferred← citeshttps://doi.org/10.1016/j.isatra.2020.09.018openalex-snapshot
Complex data labeling with deep learning methods: Lessons from fisheries acoustics
inferred← citeshttps://doi.org/10.1021/acsomega.5c09956openalex-snapshot
Integration of Multiframe and Multichannel Residual Attention Models for Mine Water Hazard Video Feature Recognition
inferred← citeshttps://doi.org/10.1108/ir-11-2023-0286openalex-snapshot
Design and extensibility analysis of a variable buoyancy system for small autonomous underwater vehicles
inferred← citeshttps://doi.org/10.1109/access.2020.2978880openalex-snapshot
Underwater Object Classification in Sidescan Sonar Images Using Deep Transfer Learning and Semisynthetic Training Data
inferred← citeshttps://doi.org/10.1109/access.2020.2995390openalex-snapshot
Deep Gabor Neural Network for Automatic Detection of Mine-Like Objects in Sonar Imagery
inferred← citeshttps://doi.org/10.1109/access.2024.3353688openalex-snapshot
Underwater Target Detection Using Deep Learning: Methodologies, Challenges, Applications, and Future Evolution
inferred← citeshttps://doi.org/10.1109/auv.2018.8729805openalex-snapshot
Hydrobatics: A Review of Trends, Challenges and Opportunities for Efficient and Agile Underactuated AUVs
inferred← citeshttps://doi.org/10.1109/dicta47822.2019.8945982openalex-snapshot
Mine-Like Object Sensing in Sonar Imagery with a Compact Deep Learning Architecture for Scarce Data
inferred← citeshttps://doi.org/10.1109/icamcs.net46018.2018.00018openalex-snapshot
Recognition of Underwater Objects Using Deep Learning in Matlab
inferred← citeshttps://doi.org/10.1109/iccsnt58790.2023.10334551openalex-snapshot
Simulated Sonar Image Generation Method Based on Improved CycleGAN
inferred← citeshttps://doi.org/10.1109/iciccs56967.2023.10142384openalex-snapshot
Machine Learning based Underwater Mine Detection
inferred← citeshttps://doi.org/10.1109/icstcc55426.2022.9931775openalex-snapshot
Marine Mine Detection Using Deep Learning
inferred← citeshttps://doi.org/10.1109/joe.2022.3152863openalex-snapshot
Target Detection and Segmentation in Circular-Scan Synthetic Aperture Sonar Images Using Semisupervised Convolutional Encoder–Decoders
inferred← citeshttps://doi.org/10.1109/jsen.2019.2925830openalex-snapshot
Crosstalk Removal in Forward Scan Sonar Image Using Deep Learning for Object Detection
inferred← citeshttps://doi.org/10.1109/jsen.2023.3324438openalex-snapshot
Deep Learning Algorithms for Sonar Imagery Analysis and Its Application in Aquaculture: A Review
inferred← citeshttps://doi.org/10.1109/lgrs.2025.3596852openalex-snapshot
Operational Assessment of Side-Scan Sonar Data Applied to Naval Mine Detection Using an Automatic Target Recognition Algorithm
inferred← citeshttps://doi.org/10.1109/mmar.2019.8864729openalex-snapshot
Selection of Training Options for Deep Learning Neural Network Using Genetic Algorithm
inferred← citeshttps://doi.org/10.1109/oceans58557.2025.11104554openalex-snapshot
Acoustic Simulated Sonar Data and Neural Networks for Marine Mine Detection
inferred← citeshttps://doi.org/10.1109/oceanskobe.2018.8559276openalex-snapshot
Use of Deep Features for the Automatic Classification of Fish Sounds
inferred← citeshttps://doi.org/10.1109/oceanslimerick52467.2023.10244721openalex-snapshot
LSTS Toolchain Framework for Deep Learning Implementation into Autonomous Underwater Vehicle
inferred← citeshttps://doi.org/10.1109/tgrs.2024.3363875openalex-snapshot
Seg2Sonar: A Full-Class Sample Synthesis Method Applied to Underwater Sonar Image Target Detection, Recognition, and Segmentation Tasks
inferred← citeshttps://doi.org/10.1109/tgrs.2024.3371051openalex-snapshot
A Sample Augmentation Method for Side-Scan Sonar Full-Class Images That Can Be Used for Detection and Segmentation
inferred← citeshttps://doi.org/10.1109/tii.2019.2946618openalex-snapshot
Underwater Internet of Things in Smart Ocean: System Architecture and Open Issues
inferred← citeshttps://doi.org/10.1109/tnnls.2022.3156620openalex-snapshot
A White-Box Testing for Deep Neural Networks Based on Neuron Coverage
inferred← citeshttps://doi.org/10.1117/12.3031638openalex-snapshot
On the use of simulated data for target recognition and mission planning
inferred← citeshttps://doi.org/10.1145/3503047.3503057openalex-snapshot
Research on Intelligent Operational Assisted Decision-making of Naval Battlefield Based on Deep Reinforcement Learning
inferred← citeshttps://doi.org/10.1371/journal.pone.0272602openalex-snapshot
Data augmentation using image translation for underwater sonar image segmentation
inferred← citeshttps://doi.org/10.17818/nm/2020/1.2openalex-snapshot
Using Pretrained AlexNet Deep Learning Neural Network for Recognition of Underwater Objects
inferred← citeshttps://doi.org/10.23919/oceans59106.2025.11245033openalex-snapshot
SonarCloud: A Simulated Forward Looking Sonar Dataset for Underwater Perception Tasks
inferred← citeshttps://doi.org/10.31414/ee.2022.d.131558openalex-snapshot
Machine learning methods for vessel type classification with underwater acoustic data
inferred← citeshttps://doi.org/10.3390/act14070340openalex-snapshot
Variable Structure Depth Controller for Energy Savings in an Underwater Device: Proof of Stability
inferred← citeshttps://doi.org/10.3390/electronics10232943openalex-snapshot
A Review of Underwater Mine Detection and Classification in Sonar Imagery
inferred← citeshttps://doi.org/10.3390/jmse11030487openalex-snapshot
Sparsity Regularization-Based Real-Time Target Recognition for Side Scan Sonar with Embedded GPU
inferred← citeshttps://doi.org/10.3390/jmse6030093openalex-snapshot
Semantic Segmentation of Underwater Imagery Using Deep Networks Trained on Synthetic Imagery
inferred← citeshttps://doi.org/10.3390/jmse9010005openalex-snapshot
Underwater Pipe and Valve 3D Recognition Using Deep Learning Segmentation
inferred← citeshttps://doi.org/10.3390/rs12183020openalex-snapshot
The Effectiveness of Using a Pretrained Deep Learning Neural Networks for Object Classification in Underwater Video
inferred← citeshttps://doi.org/10.3390/s22062181openalex-snapshot
A Survey of Underwater Acoustic Data Classification Methods Using Deep Learning for Shoreline Surveillance
inferred← citeshttps://doi.org/10.3390/s22218141openalex-snapshot
Real-Time Pipe and Valve Characterisation and Mapping for Autonomous Underwater Intervention Tasks
inferred← citeshttps://doi.org/10.3390/s22239536openalex-snapshot
Sea Mine Detection Framework Using YOLO, SSD and EfficientDet Deep Learning Models
inferred← citeshttps://doi.org/10.4018/978-1-6684-9324-3.ch010openalex-snapshot
The Use of Artificial Intelligence in Digital Marketing Competitive Strategies and Tactics
inferred← citeshttps://doi.org/10.48550/arxiv.1810.07990openalex-snapshot
Deep Learning from Shallow Dives: Sonar Image Generation and Training for Underwater Object Detection
inferred← citeshttps://doi.org/10.48550/arxiv.2107.10504openalex-snapshot
External-Memory Networks for Low-Shot Learning of Targets in Forward-Looking-Sonar Imagery
inferred← citeshttps://doi.org/10.5194/isprs-annals-v-2-2020-657-2020openalex-snapshot
INVESTIGATING FULLY CONVOLUTIONAL NETWORK TO SEMANTIC LABELLING OF BATHYMETRIC POINT CLOUD
inferred← citeshttps://doi.org/10.54097/ajst.v7i2.11779openalex-snapshot
Application Field and Development Trend of Small Autonomous Underwater Vehicle
inferred← citeshttps://doi.org/10.70675/37ed465dzd027z4358z94a3z33afcee96511openalex-snapshot
Study of data augmentation for deep neural networks robustness
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