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Automated Detection of Oil Spills in Images: Combining a Novel Feature Extraction Technique Based on the Qexponential Distribution with Machine Learning Models
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1 of the 55 references listed on this page is in the Retraction Watch database as retracted (export 2026-11-04): 10.1155/2022/7348344 (notice 2023-12-29).
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Outgoing claims: the papers this work cites, builds on, or argues with.
inferredcites →https://doi.org/10.1007/978-3-030-05710-7_35openalex-extracted
Early Identification of Oil Spills in Satellite Images Using Deep CNNs
inferredcites →https://doi.org/10.1007/978-3-030-17795-9_10openalex-extracted
Deep Learning vs. Traditional Computer Vision
inferredcites →https://doi.org/10.1007/978-3-031-01552-6openalex-extracted
Learning with Support Vector Machines
inferredcites →https://doi.org/10.1007/s00267-010-9447-9openalex-extracted
Planning for the Human Dimensions of Oil Spills and Spill Response
inferredcites →https://doi.org/10.1007/s00477-022-02219-wopenalex-extracted
Spatio-temporal estimation of wind speed and wind power using extreme learning machines: predictions, uncertainty and technical potential
inferredcites →https://doi.org/10.1007/s11042-021-10783-6openalex-extracted
Automatic prediction of COVID− 19 from chest images using modified ResNet50
inferredcites →https://doi.org/10.1016/0031-3203(95)00067-4openalex-extracted
A comparative study of texture measures with classification based on featured distributions
inferredcites →https://doi.org/10.1016/b978-0-12-409548-9.11156-xopenalex-extracted
Other Environmental Health Issues: Oil Spill
inferredcites →https://doi.org/10.1016/b978-0-12-809399-3.00010-0openalex-extracted
Petroleum Industry Activities and Human Health
inferredcites →https://doi.org/10.1016/j.asoc.2019.105716openalex-extracted
Oil spill segmentation in SAR images using convolutional neural networks. A comparative analysis with clustering and logistic regression algorithms
inferredcites →https://doi.org/10.1016/j.cageo.2016.12.013openalex-extracted
On the use of feature selection to improve the detection of sea oil spills in SAR images
inferredcites →https://doi.org/10.1016/j.cie.2018.11.008openalex-extracted
A new approach to oil spill detection that combines deep learning with unmanned aerial vehicles
inferredcites →https://doi.org/10.1016/j.csda.2010.09.029openalex-extracted
Dealing with monotone likelihood in a model for speckled data
inferredcites →https://doi.org/10.1016/j.enmm.2020.100305openalex-extracted
Environmental impacts of oil spills and their remediation by magnetic nanomaterials
inferredcites →https://doi.org/10.1016/j.imavis.2012.01.001openalex-extracted
Extended local binary patterns for texture classification
inferredcites →https://doi.org/10.1016/j.jenvman.2023.118833openalex-extracted
Development of rapid and effective oil-spill response system integrated with oil collection, recovery and storage devices for small oil spills at initial stage: From lab-scale study to field-scale test
inferredcites →https://doi.org/10.1016/j.jenvman.2024.120246openalex-extracted
Innovative approach for predicting daily reference evapotranspiration using improved shallow and deep learning models in a coastal region: A comparative study
inferredcites →https://doi.org/10.1016/j.jfoodeng.2005.11.030openalex-extracted
A classification system for beans using computer vision system and artificial neural networks
inferredcites →https://doi.org/10.1016/j.jlp.2022.104912openalex-extracted
Oil spills characteristics, detection, and recovery methods: A systematic risk-based view
inferredcites →https://doi.org/10.1016/j.marpolbul.2016.06.027openalex-extracted
Environmental effects of the Deepwater Horizon oil spill: A review
inferredcites →https://doi.org/10.1016/j.ress.2019.106787openalex-extracted
Reliability data analysis of systems in the wear-out phase using a (corrected) q-Exponential likelihood
inferredcites →https://doi.org/10.1016/j.ress.2020.107370openalex-extracted
Towards a modification of a regulatory framework aiming at bunker oil spill prevention from ships – A design aspect of bunker tanks vents location guided by CFD simulations
inferredcites →https://doi.org/10.1016/j.rse.2004.11.015openalex-extracted
Oil spill detection by satellite remote sensing
inferredcites →https://doi.org/10.1016/j.rse.2010.04.009openalex-extracted
Dark-spot detection from SAR intensity imagery with spatial density thresholding for oil-spill monitoring
inferredcites →https://doi.org/10.1016/j.ssci.2019.09.011openalex-extracted
Dynamic assessment of safety barriers preventing escalation in offshore Oil&Gas
inferredcites →https://doi.org/10.1080/13683500.2020.1760222openalex-extracted
Blue water turns black: economic impact of oil spill on tourism and fishing in Brazilian Northeast
inferredcites →https://doi.org/10.1103/physreve.90.062809openalex-extracted
Universal behavior of the interoccurrence times between losses in financial markets: Independence of the time resolution
inferredcites →https://doi.org/10.1109/eict48899.2019.9068805openalex-extracted
Transfer Learning Based Plant Diseases Detection Using ResNet50
inferredcites →https://doi.org/10.1109/ist.2017.8261559openalex-extracted
Polarimetric SAR oil spill detection based on deep networks
inferredcites →https://doi.org/10.1109/jstars.2013.2251864openalex-extracted
Satellite Oil Spill Detection Using Artificial Neural Networks
inferredcites →https://doi.org/10.1109/tip.2020.3031813openalex-extracted
Low-Rank Preserving t-Linear Projection for Robust Image Feature Extraction
inferredcites →https://doi.org/10.1109/tip.2020.3038363openalex-extracted
PWD-3DNet: A Deep Learning-Based Fully-Automated Segmentation of Multiple Structures on Temporal Bone CT Scans
inferredcites →https://doi.org/10.1109/tip.2020.3042083openalex-extracted
Interpreting and Improving Adversarial Robustness of Deep Neural Networks With Neuron Sensitivity
inferredcites →https://doi.org/10.1109/tip.2021.3050668openalex-extracted
Panoptic Feature Fusion Net: A Novel Instance Segmentation Paradigm for Biomedical and Biological Images
inferredcites →https://doi.org/10.1109/tpami.2011.274openalex-extracted
SAR Image Segmentation Based on Level Set Approach and {\cal G}_A^0 Model
inferredcites →https://doi.org/10.1155/2020/8909458openalex-extracted
Automatic Image Captioning Based on ResNet50 and LSTM with Soft Attention
inferredcites →https://doi.org/10.1155/2021/5843816openalex-extracted
Satellite and Scene Image Classification Based on Transfer Learning and Fine Tuning of ResNet50
inferredcites →https://doi.org/10.1155/2022/7348344openalex-extracted
[Retracted] Enhanced Watershed Segmentation Algorithm‐Based Modified ResNet50 Model for Brain Tumor Detection
inferredcites →https://doi.org/10.1214/aos/1176345513openalex-extracted
Logistic Regression Diagnostics
inferredcites →https://doi.org/10.1371/journal.pone.0247839openalex-extracted
Convolutional neural network model based on radiological images to support COVID-19 diagnosis: Evaluating database biases
inferredcites →https://doi.org/10.1590/0102-311x00230319openalex-extracted
Artisanal fishers, consumers and the environment: immediate consequences of the oil spill in Pernambuco, Northeast Brazil
inferredcites →https://doi.org/10.23919/ccc50068.2020.9189408openalex-extracted
The Surface Damage Identifications of Wind Turbine Blades Based on ResNet50 Algorithm
inferredcites →https://doi.org/10.3389/fpubh.2018.00117openalex-extracted
The Development of Long-Term Adverse Health Effects in Oil Spill Cleanup Workers of the Deepwater Horizon Offshore Drilling Rig Disaster
inferredcites →https://doi.org/10.3390/e21040430openalex-extracted
A q-Extension of Sigmoid Functions and the Application for Enhancement of Ultrasound Images
inferredcites →https://doi.org/10.3390/rs11151762openalex-extracted
Oil Spill Identification from Satellite Images Using Deep Neural Networks
inferredcites →https://doi.org/10.3390/rs12061015openalex-extracted
A Deep Convolutional Neural Network for Oil Spill Detection from Spaceborne SAR Images
inferredcites →https://doi.org/10.3390/rs12213647openalex-extracted
Oil Spill Detection and Mapping: A 50-Year Bibliometric Analysis
inferredcites →https://doi.org/10.3390/rs12244090openalex-extracted
Oil Spill Detection Using Machine Learning and Infrared Images
inferredcites →https://doi.org/10.3390/s18030797openalex-extracted
Segmentation of Oil Spills on Side-Looking Airborne Radar Imagery with Autoencoders
inferredcites →https://doi.org/10.7901/2169-3358-2001-1-591openalex-extracted
A Review of the Problems Posed By Spills of Heavy Fuel Oils
inferredcites →https://doi.org/10.9781/ijimai.2016.415openalex-extracted
Multilayer Perceptron: Architecture Optimization and Training
inferredcites →https://doi.org/10.48550/arxiv.1603.02754openalex-snapshot
XGBoost: A Scalable Tree Boosting System
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