Sediment Classification of Small-Size Seabed Acoustic Images Using Convolutional Neural Networks
IEEE Access, 2019 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 +3 more sources
Small-Sample Seabed Sediment Classification Based on Deep Learning
Remote Sensing, 2023 Seabed sediment classification is of great significance in acoustic remote sensing. To accurately classify seabed sediments, big data are needed to train the classifier.
Yuxin Zhao +4 more
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Geosciences, 2018 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 +3 more sources
Validating deep learning seabed classification via acoustic similarity [PDF]
JASA Express Letters, 2021 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
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Optimizing the Sediment Classification of Small Side-Scan Sonar Images Based on Deep Learning
IEEE Access, 2021 Acoustic seabed classification (ASC) is a fast and large-scale seabed sediment survey method. In particular, combining it with an automated classifier can theoretically achieve fast automatic seabed sediment classification.
Xiaoming Qin +3 more
doaj +1 more source
Analysis of some problems in classification of seabed bottom characteristics using acoustic backscattering intensity [PDF]
E3S Web of Conferences, 2020 The backscattering intensity collected by multi beam sonar system and scanning sonar system can be used to classify seabed bottom characteristics. However, there are many problems that have not been solved in the practical application.
Jintao FENG +4 more
doaj +1 more source
Journal of Marine Science and Engineering, 2021 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
Frontiers in Remote Sensing, 2022 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
Seabed classification and source localization with Gaussian processes and machine learning [PDF]
JASA Express Letters, 2022 Workshop '97 data are employed for seabed classification and source range estimation. The data are acoustic fields computed at vertically separated receivers for various ranges and different environments.
Christina Frederick +1 more
doaj +1 more source
Assessing the use of harmonized multisource backscatter data for thematic benthic habitat mapping
Science of Remote Sensing, 2021 Legacy seabed mapping datasets are increasingly common as the need for detailed seabed information is recognized. Acoustic backscatter data from multibeam echosounders can be a useful surrogate for seabed properties and are commonly used for benthic ...
Benjamin Misiuk +2 more
doaj +1 more source