Results 11 to 20 of about 1,817,988 (202)
Seabed Sediment Classification Using Spatial Statistical Characteristics
Conventional sediment classification methods based on Multibeam Echo System (MBES) data have low accuracy since the correlation between features and sediment has not been fully considered.
Quanyin Zhang +3 more
doaj +2 more sources
Seabed Protection Systems to prevent Scour from High-Speed Ships [PDF]
This document reviews the scour protection systems required around port structures where these are to be used for the berthing of vessels powered by water jet systems.
Evans, G.
core +7 more sources
The exploitation and utilization of seabed sediments provide vital significance in many fields. Recently, the classification of seabed sediments using sub-bottom profiler(SBP) data has become a research focus.
Mingke Li +3 more
doaj +1 more source
The upper part of the Krka River estuary and Prokljan Lake are a specific example of a well-stratified estuarine environment in a submerged river canyon.
Ozren Hasan +5 more
doaj +1 more source
The modern discrimination of sediment is based on acoustic intensity (backscatter) information from high-resolution multibeam echo-sounder systems (MBES).
Xiaochen Yu +4 more
doaj +1 more source
Applying a Multi-Method Framework to Analyze the Multispectral Acoustic Response of the Seafloor
Improvements to acoustic seafloor mapping systems have motivated novel marine geological and benthic biological research. Multibeam echosounders (MBES) have become a mainstream tool for acoustic remote sensing of the seabed.
Pedro S. Menandro +3 more
doaj +1 more source
Multi-frequency backscatter data collected from multibeam echosounders (MBESs) is increasingly becoming available. The ability to collect data at multiple frequencies at the same time is expected to allow for better discrimination between seabed ...
Timo C. Gaida +5 more
doaj +1 more source
Sediment Classification of Small-Size Seabed Acoustic Images Using Convolutional Neural Networks
Seabed acoustic images are image data mosaics derived from seafloor acoustic backscattering intensity data, which is related to the type of sediment covering the seabed.
Xiaowen Luo +5 more
doaj +1 more source
Validating deep learning seabed classification via acoustic similarity [PDF]
While seabed characterization methods have often focused on estimating individual sediment parameters, deep learning suggests a class-based approach focusing on the overall acoustic effect.
David J. Forman +3 more
doaj +1 more source
Selecting Optimal Random Forest Predictive Models: A Case Study on Predicting the Spatial Distribution of Seabed Hardness. [PDF]
Spatially continuous predictions of seabed hardness are important baseline environmental information for sustainable management of Australia's marine jurisdiction.
Jin Li, Maggie Tran, Justy Siwabessy
doaj +1 more source

