Seabed sediment classification using multibeam backscatter data based on the selecting optimal random forest model
Sign Up to like & getrecommendations! Published in 2020 at "Applied Acoustics"
DOI: 10.1016/j.apacoust.2020.107387
Abstract: Abstract Seabed sediment classification using acoustic remote sensing technique is an attractive approach due to its high coverage capabilities and limited costs compared to taking samples of the seafloor. This paper focuses on backscatter intensity… read more here.
Keywords: classification; sediment classification; seabed sediment; intensity ... See more keywords
DNN-based seabed classification using differently weighted MBES multifeatures
Sign Up to like & getrecommendations! Published in 2021 at "Marine Geology"
DOI: 10.1016/j.margeo.2021.106519
Abstract: Abstract Seabed sediment classification has significance for the utilization of marine resources and marine scientific research. Currently, the multibeam echo sounder (MBES) is increasingly becoming the tool of choice for large-scale seabed sediment classification. To… read more here.
Keywords: mbes multifeatures; seabed sediment; backscatter mosaic; sediment classification ... See more keywords
Probabilistic neural network based seabed sediment recognition method for side-scan sonar imagery
Sign Up to like & getrecommendations! Published in 2020 at "Sedimentary Geology"
DOI: 10.1016/j.sedgeo.2020.105792
Abstract: Abstract Recognition of seabed sediment is one of the critical foundations of marine exploitation. This paper proposes a probabilistic neural network (PNN) based method to improve the identification accuracy of seabed sediment from side-scan sonar… read more here.
Keywords: side scan; seabed sediment; sonar imagery; scan sonar ... See more keywords
Research on Seabed Sediment Classification Based on the MSC-Transformer and Sub-Bottom Profiler
Sign Up to like & getrecommendations! Published in 2023 at "Journal of Marine Science and Engineering"
DOI: 10.3390/jmse11051074
Abstract: This paper proposed an MSC-Transformer model based on the Transformer’s neural network, which was applied to seabed sediment classification. The data came from about 2900 km2 of seabed area on the northern slope of the… read more here.
Keywords: sub bottom; seabed sediment; sediment classification; msc transformer ... See more keywords