A Novel Iterative Estimation Technique Using Radar Sensing to Remotely Characterize Oil Slicks During Spills
Author:
Affiliation:
1. Rheinland-Pfälzische Technische Universität (RPTU),Microelectronic Systems Design Research Group (EMS), EIT,Kaiserslautern,Germany
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/10281394/10281399/10281663.pdf?arnumber=10281663
Reference18 articles.
1. Source identification of sea surface oil with geochemical data in Cantarell, Mexico
2. Design and Implementation of a Coastal-Mounted Sensor for Oil Film Detection on Seawater
3. Machine Learning Using Support Vector Regression in Radar Remote Sensing for Oil-Spill Thickness Estimation
4. Oil Thickness Estimation Using Single- and Dual- Frequency Maximum-Likelihood Approach
5. Identifying Oil Spill Types Based on Remotely Sensed Reflectance Spectra and Multiple Machine Learning Algorithms
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