Learning Seabed Properties and Sensitivities from Ship Noise Spectrograms
OCEANS 2024 - SINGAPORE（2024）
Key words
Spectroscopic,Neural Network,Deep Neural Network,Validity Of The Results,Information Content,Parameter Sensitivity,Speed Of Sound,Relative Uncertainty,Sediment Layers,Cramer-Rao Lower Bound,Sediment Properties,Root Mean Square Error,Parameter Estimates,Deep Learning,Training Dataset,Parameter Uncertainty,Prediction Uncertainty,Mean Absolute Percentage Error,Transmission Loss,Single Label,Residual Neural Network,Ship Speed,Sediment Type,Source Depth,Sound Propagation
AI Read Science
Must-Reading Tree
Example
Generate MRT to find the research sequence of this paper
Chat Paper
Summary is being generated by the instructions you defined