Results 91 to 100 of about 4,776 (292)

Human‐in‐the‐Loop Swarms: A Bionic Swarm Approach to Real‐World Soil Mapping

Advanced Intelligent Systems, EarlyView.
This article introduces the “Bionic Swarm,” a novel system that lowers the barriers to real‐world swarm validation by abstracting difficult hardware tasks to app‐guided human agents. We demonstrate the system's utility through the experimental validation of a geotechnical soil‐mapping swarm algorithm and show superior performance to baseline approaches
Petras Swissler, Mohammadali Rashidioun, Nicholas Sahu, Raaid Kabir, Ayodeji Aderibigbe, Oladoyin Kolawole   +5 more
wiley   +1 more source

A Novel Oil Spill Dataset Augmentation Framework Using Object Extraction and Image Blending Techniques

Remote Sensing
Oil spills pose significant threats to marine and coastal ecosystems, biodiversity and local economies, necessitating efficient and accurate detection systems.
Farkhod Akhmedov, Halimjon Khujamatov, Mirjamol Abdullaev, Heung-Seok Jeon   +3 more
doaj   +1 more source

Preliminary Empirical Assessment of Offshore Production Platforms in the Gulf of Mexico [PDF]

This paper reports on a preliminary analysis of performance indicators on 3,020 platforms operating in the Gulf of Mexico between 1996 and 2010. Statistical analysis reveals that company-reported incidents (such as blowouts, fires, injuries, and ...
Cohen, Mark A., Muehlenbachs, Lucija, Gerarden, Todd   +2 more
core  

A Dual-Branch EfficientNetV2-S-Based Method for Marine Oil Spill Detection Using Multisource Satellite Data Fusion

IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
As one of the most severe forms of pollution, oil spills pose significant threats to the marine environment. Synthetic aperture radar (SAR), an active microwave remote sensing technology, enables sea surface monitoring under all weather and lighting ...
Yong Wan, Liyan Peng, Rui Zhang, Ruyue Zhang, Haowen Wang   +4 more
doaj   +1 more source

Semi-Automatic Oil Spill Detection on X-Band Marine Radar Images Using Texture Analysis, Machine Learning, and Adaptive Thresholding

Remote Sensing, 2019
Oil spills bring great damage to the environment and, in particular, to coastal ecosystems. The ability of identifying them accurately is important to prompt oil spill response.
Peng Liu, Ying Li, Bingxin Liu, Peng Chen, Jin Xu   +4 more
doaj   +1 more source

Real time geo-referenced detection of dispersed oil plumes

, 2005
pgs. 11168-11171The current SMART protocol used by the U.S. Coast Guard relies on traditional ex-situ fluorometers that require physical transport of the sample from the water column to the instruments.
Page, CA, Kelly, F, Bonner, JS, Ojo, T, Fuller, CB   +4 more
core  

Advances in Remote Sensing Research on Oil and Ice from the IOGP Arctic Oil Spill Response Technology JIP

, 2017
(2017-044) The IOGP Arctic Oil Spill Response Technology Joint Industry Program’s Remote Sensing Technical Working Group was initiated in 2012 with the objective to expand the oil industry’s detection and monitoring capabilities for spills
David Palandro, Joseph Mullin
core   +1 more source

Comparative Analysis between ResNet Models on Marine Oil spill detection

, 2023
Marine oil spills remain a significant threat to ecosystems and maritime safety, necessitating advanced detection methodologies. Despite a decrease in the frequency of spills, challenges exist in timely and accurate detection.
Joseph, Abin
core  

Dark Spot Detection in SAR Images of Oil Spill Using Segnet

Applied Sciences, 2018
Damping Bragg scattering from the ocean surface is the basic underlying principle of synthetic aperture radar (SAR) oil slick detection, and they produce dark spots on SAR images.
Hao Guo, Guo Wei, Jubai An
doaj   +1 more source

Oil spill detection on X-band marine radar images based on sea clutter fitting model. [PDF]

Heliyon, 2023
Liu P, Liu B, Li Y, Chen P, Xu J.
europepmc   +1 more source