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Segmentation of Oil Spills on Side-Looking Airborne Radar Imagery with Autoencoders

https://doi.org/10.3390/s18030797
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Outgoing claims: the papers this work cites, builds on, or argues with.

inferredcites →https://doi.org/10.1007/978-3-7908-2604-3_16openalex-snapshot
Large-Scale Machine Learning with Stochastic Gradient Descent
inferredcites →https://doi.org/10.1007/s12524-016-0553-xopenalex-snapshot
Optimum Features Selection for oil Spill Detection in SAR Image
inferredcites →https://doi.org/10.1016/0167-8655(95)00128-xopenalex-snapshot
Radar image segmentation using recurrent artificial neural networks
inferredcites →https://doi.org/10.1016/j.cageo.2016.12.013openalex-snapshot
On the use of feature selection to improve the detection of sea oil spills in SAR images
inferredcites →https://doi.org/10.1016/j.eswa.2017.07.002openalex-snapshot
Staff-line removal with selectional auto-encoders
inferredcites →https://doi.org/10.1016/j.isprsjprs.2007.05.003openalex-snapshot
Detection and discrimination between oil spills and look-alike phenomena through neural networks
inferredcites →https://doi.org/10.1016/j.isprsjprs.2012.01.005openalex-snapshot
Oil spill feature selection and classification using decision tree forest on SAR image data
inferredcites →https://doi.org/10.1016/j.marpolbul.2014.03.059openalex-snapshot
Review of oil spill remote sensing
inferredcites →https://doi.org/10.1016/j.rse.2012.03.024openalex-snapshot
State of the art satellite and airborne marine oil spill remote sensing: Application to the BP Deepwater Horizon oil spill
inferredcites →https://doi.org/10.1016/j.rse.2013.10.012openalex-snapshot
A comparative study of different classification techniques for marine oil spill identification using RADARSAT-1 imagery
inferredcites →https://doi.org/10.1023/b:visi.0000022288.19776.77openalex-snapshot
Efficient Graph-Based Image Segmentation
inferredcites →https://doi.org/10.1029/2011eo060001openalex-snapshot
Tracking the Deepwater Horizon Oil Spill: A Modeling Perspective
inferredcites →https://doi.org/10.1029/2011gm001113openalex-snapshot
Studies of the Deepwater Horizon Oil Spill With the UAVSAR Radar
inferredcites →https://doi.org/10.1029/gm195openalex-snapshot
Monitoring and Modeling the Deepwater Horizon Oil Spill: A Record‐Breaking Enterprise
inferredcites →https://doi.org/10.1038/nature14539openalex-snapshot
Deep learning
inferredcites →https://doi.org/10.1080/01431160801891770openalex-snapshot
Dark formation detection using neural networks
inferredcites →https://doi.org/10.1109/34.946985openalex-snapshot
Unsupervised segmentation of color-texture regions in images and video
inferredcites →https://doi.org/10.1109/36.868885openalex-snapshot
Neural networks for oil spill detection using ERS-SAR data
inferredcites →https://doi.org/10.1109/cvpr.2017.632openalex-snapshot
Image-to-Image Translation with Conditional Adversarial Networks
inferredcites →https://doi.org/10.1109/cvprw.2014.79openalex-snapshot
Generalized Autoencoder: A Neural Network Framework for Dimensionality Reduction
inferredcites →https://doi.org/10.1109/jstars.2013.2251864openalex-snapshot
Satellite Oil Spill Detection Using Artificial Neural Networks
inferredcites →https://doi.org/10.1109/jstars.2016.2559946openalex-snapshot
A Combination of Traditional and Polarimetric Features for Oil Spill Detection Using TerraSAR-X
inferredcites →https://doi.org/10.1109/jstars.2017.2740979openalex-snapshot
A Backscattering-Suppression-Based Variational Level-Set Method for Segmentation of SAR Oil Slick Images
inferredcites →https://doi.org/10.1109/lgrs.2007.907174openalex-snapshot
Classifiers and Confidence Estimation for Oil Spill Detection in ENVISAT ASAR Images
inferredcites →https://doi.org/10.1109/tgrs.2013.2287916openalex-snapshot
Characterization of Marine Surface Slicks by Radarsat-2 Multipolarization Features
inferredcites →https://doi.org/10.1109/tgrs.2013.2297193openalex-snapshot
Oil Spill Detection in Hybrid-Polarimetric SAR Images
inferredcites →https://doi.org/10.1117/12.2239257openalex-snapshot
An approach for SLAR images denoising based on removing regions with low visual quality for oil spill detection
inferredcites →https://doi.org/10.1145/1390156.1390294openalex-snapshot
Extracting and composing robust features with denoising autoencoders
inferredcites →https://doi.org/10.1145/3065386openalex-snapshot
ImageNet classification with deep convolutional neural networks
inferredcites →https://doi.org/10.1186/1687-6180-2012-107openalex-snapshot
Development of band ratioing algorithms and neural networks to detection of oil spills using Landsat ETM+ data
inferredcites →https://doi.org/10.3390/app7020193openalex-snapshot
Comparison of Oil Spill Classifications Using Fully and Compact Polarimetric SAR Images
inferredcites →https://doi.org/10.3390/app7100968openalex-snapshot
Application of Deep Networks to Oil Spill Detection Using Polarimetric Synthetic Aperture Radar Images
inferredcites →https://doi.org/10.3390/proceedings1080820openalex-snapshot
Oil Slicks Detection in SLAR Images with Autoencoders
inferredcites →https://doi.org/10.3390/rs10010016openalex-snapshot
Remote Sensing Image Classification Based on Stacked Denoising Autoencoder
inferredcites →https://doi.org/10.3390/s141222798openalex-snapshot
Adaptive Weibull Multiplicative Model and Multilayer Perceptron Neural Networks for Dark-Spot Detection from SAR Imagery
inferredcites →https://doi.org/10.3390/s17010192openalex-snapshot
Synthetic Aperture Radar Target Recognition with Feature Fusion Based on a Stacked Autoencoder
inferredcites →https://doi.org/10.3390/s17081837openalex-snapshot
Discrimination of Oil Slicks and Lookalikes in Polarimetric SAR Images Using CNN
inferredcites →https://doi.org/10.3390/s18010091openalex-snapshot
A Review of Oil Spill Remote Sensing
inferredcites →https://doi.org/10.3390/s18010151openalex-snapshot
Oil Spill Detection in Terma-Side-Looking Airborne Radar Images Using Image Features and Region Segmentation
inferredcites →https://doi.org/10.3390/s18010173openalex-snapshot
Radar HRRP Target Recognition Based on Stacked Autoencoder and Extreme Learning Machine
inferredcites →https://doi.org/10.3844/jcssp.2006.735.739openalex-snapshot
Data Mining: A Preprocessing Engine
inferredcites →https://doi.org/10.48550/arxiv.1305.6663openalex-snapshot
Generalized Denoising Auto-Encoders as Generative Models
inferredcites →https://doi.org/10.48550/arxiv.1502.03167openalex-snapshot
Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift
inferredcites →https://doi.org/10.48550/arxiv.1603.09056openalex-snapshot
Image Restoration Using Very Deep Convolutional Encoder-Decoder Networks with Symmetric Skip Connections
inferredcites →https://doi.org/10.5220/0006187103720377openalex-snapshot
Candidate Oil Spill Detection in SLAR Data - A Recurrent Neural Network-based Approach
inferredcites →https://doi.org/10.5220/0006191504420447openalex-snapshot
Oil Spill Detection using Segmentation based Approaches
inferredcites →https://doi.org/10.5244/c.28.6openalex-snapshot
Return of the Devil in the Details: Delving Deep into Convolutional Nets
inferredcites →https://doi.org/10.5281/zenodo.19712698openalex-snapshot
A Study of Cross-Validation and Bootstrap for Accuracy Estimation and Model Selection
inferredcites →https://doi.org/10.5555/1756006.1953039openalex-snapshot
Stacked Denoising Autoencoders: Learning Useful Representations in a Deep Network with a Local Denoising Criterion

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.4767296openalex-extracted
Automated Detection of Oil Spills in Images: Combining a Novel Feature Extraction Technique Based on the Qexponential Distribution with Machine Learning Models
inferred← citeshttps://doi.org/10.56042/ijms.v52i01.5438zenodo-depositor-declared
Application of CNN based image classification technique for oil spill detection
inferred← citeshttps://doi.org/10.1002/9781394261567.ch13openalex-snapshot
Exploring the Depths: Satellite Image Processing and Artificial Intelligence in the Oil and Gas Industry
inferred← citeshttps://doi.org/10.1007/978-3-031-22356-3_6openalex-snapshot
Automatic Detection of Oil Spills from SAR Images Using Deep Learning
inferred← citeshttps://doi.org/10.1007/978-3-031-71836-6_16openalex-snapshot
Oil Pollution Hazards Assessments Using Remote Sensing Techniques in the Northwestern Arabian Gulf: Perspectives on Natural Oil Seepages and Anthropogenic Oil Spills
inferred← citeshttps://doi.org/10.1007/978-981-97-7502-6_6openalex-snapshot
Oil Spill Detection in SAR Images: A U-Net Semantic Segmentation Framework with Multiple Backbones
inferred← citeshttps://doi.org/10.1016/j.engappai.2022.105188openalex-snapshot
Efficient gesture recognition for the assistance of visually impaired people using multi-head neural networks
inferred← citeshttps://doi.org/10.1016/j.eti.2025.104572openalex-snapshot
Current situation and future outlook petroleum hydrocarbons in marine systems: A review
inferred← citeshttps://doi.org/10.1016/j.isprsjprs.2020.07.011openalex-snapshot
A novel deep learning instance segmentation model for automated marine oil spill detection
inferred← citeshttps://doi.org/10.1016/j.jag.2022.102695openalex-snapshot
Deep-water oil-spill monitoring and recurrence analysis in the Brazilian territory using Sentinel-1 time series and deep learning
inferred← citeshttps://doi.org/10.1016/j.marpolbul.2020.111921openalex-snapshot
Marine oil spill detection using Synthetic Aperture Radar over Indian Ocean
inferred← citeshttps://doi.org/10.1080/10916466.2024.2357699openalex-snapshot
Research on the PDC rock cuttings image instance segmentation method based on improved U-Net++ network and multi-feature fusion
inferred← citeshttps://doi.org/10.1080/15275922.2019.1597781openalex-snapshot
Marine Radar Oil-Spill Monitoring through Local Adaptive Thresholding
inferred← citeshttps://doi.org/10.1109/access.2019.2929080openalex-snapshot
Precise Ship Location With CNN Filter Selection From Optical Aerial Images
inferred← citeshttps://doi.org/10.1109/icarm.2019.8834281openalex-snapshot
Visually Interpretable Profile Extraction with an Autoencoder for Health Monitoring of Industrial Systems
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Autonomous oil spill and pollution detection for large-scale conservation in marine eco-cyber-physical systems
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Ground Target Classification in Noisy SAR Images Using Convolutional Neural Networks
inferred← citeshttps://doi.org/10.1117/12.2598032openalex-snapshot
Automatic offshore oil slick detection based on deep learning using SAR data and contextual information
inferred← citeshttps://doi.org/10.21203/rs.3.rs-2263261/v1openalex-snapshot
Automated detection of oil spills in images: combining a novel feature extraction technique based on the q- Exponential distribution with machine learning models
inferred← citeshttps://doi.org/10.3389/fmech.2026.1919085openalex-snapshot
Explainable deep learning with novel marine domain metrics for oil spill detection
inferred← citeshttps://doi.org/10.3390/data10070117openalex-snapshot
LADOS: Aerial Imagery Dataset for Oil Spill Detection, Classification, and Localization Using Semantic Segmentation
inferred← citeshttps://doi.org/10.3390/electronics12061300openalex-snapshot
ASA-DRNet: An Improved Deeplabv3+ Framework for SAR Image Segmentation
inferred← citeshttps://doi.org/10.3390/jmse11071406openalex-snapshot
Deep Learning-Based Approaches for Oil Spill Detection: A Bibliometric Review of Research Trends and Challenges
inferred← citeshttps://doi.org/10.3390/rs11121402openalex-snapshot
Semantic Segmentation of SLAR Imagery with Convolutional LSTM Selectional AutoEncoders
inferred← citeshttps://doi.org/10.3390/rs11141698openalex-snapshot
Oil Spill Segmentation in Ship-Borne Radar Images with an Improved Active Contour Model
inferred← citeshttps://doi.org/10.3390/rs12061015openalex-snapshot
A Deep Convolutional Neural Network for Oil Spill Detection from Spaceborne SAR Images
inferred← citeshttps://doi.org/10.3390/rs12203338openalex-snapshot
Sensors, Features, and Machine Learning for Oil Spill Detection and Monitoring: A Review
inferred← citeshttps://doi.org/10.3390/rs12203416openalex-snapshot
Advances in Remote Sensing Technology, Machine Learning and Deep Learning for Marine Oil Spill Detection, Prediction and Vulnerability Assessment
inferred← citeshttps://doi.org/10.3390/rs13122378openalex-snapshot
Oil Spill Detection with Multiscale Conditional Adversarial Networks with Small-Data Training
inferred← citeshttps://doi.org/10.3390/rs13183606openalex-snapshot
Oil Spill Identification from SAR Images for Low Power Embedded Systems Using CNN
inferred← citeshttps://doi.org/10.3390/rs14020264openalex-snapshot
BO-DRNet: An Improved Deep Learning Model for Oil Spill Detection by Polarimetric Features from SAR Images
inferred← citeshttps://doi.org/10.3390/rs14153565openalex-snapshot
Offshore Oil Slick Detection: From Photo-Interpreter to Explainable Multi-Modal Deep Learning Models Using SAR Images and Contextual Data
inferred← citeshttps://doi.org/10.3390/rs17020336openalex-snapshot
A Novel Oil Spill Dataset Augmentation Framework Using Object Extraction and Image Blending Techniques
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IR-UWB Pulse Generation Using FPGA Scheme for through Obstacle Human Detection
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A Deep-Learning Framework for the Detection of Oil Spills from SAR Data
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AUTOMATED MARINE OIL SPILL DETECTION USING DEEP LEARNING INSTANCE SEGMENTATION MODEL
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Hydrographic data inspection and disaster monitoring using shipborne radar small range images with electronic navigation chart
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