Machine learning for ocean sound sources and environment

Using underwater sound pressure from active and passive sources to train machine learning models for various applications.
Type of Data: 
acoustic data
Approximate Data Size: 
1 TB
Domain Expert: 
Emma Ozanich
Domain Student: 
Emma Ozanich
Methods Expert: 
Peter Gerstoft
Methods Student Openings: 
2.00
Methods Student Funding: 
no
Methods Student Prerequisites: 
One course in signal processing. Experience with python. MS or PhD student preferred.