machine learning

Machine learning in fisheries acoustics

Accelerating information extraction from fisheries acoustic data through a cloud-based machine learning workflow.

Pattern discovery from long-term echosounder time series

Developing algorithms to discover prominent spatio-temporal patterns of animal movement and grouping behavior observed in sonar echoes using data from the Ocean Observatories Initiative (OOI).

Investigation of duty cycles for measuring activity in passive acoustic bat monitoring

Variability and influence of fisheries acoustic echogram annotations on machine learning applications

High-frequency echosounders are the workhorse in fisheries and marine ecological surveys. Due to the inherent complexity of biological aggregations and ambiguity in interpreting echoes from species of similar size and anatomical compositions, …

Two Pieces of the Same Puzzle: Active and Passive Acoustics for Cross-Trophic Marine Ecosystem Monitoring Part II

In this presentation, I will discuss fundamental concepts of using active acoustic techniques as a remote sensing tool to observe mid-trophic level fish and zooplankton in the ocean. These observations complement passive acoustic measurements that …

Investigation of duty cycles in passive acoustic bat monitoring

Understanding echoes

Keynote Lecture at the 2022 Denver Acoustical Society of America meeting.

Discerning behavioral habits of echolocating bats using acoustical and computational methods

Summarizing low-dimensional patterns in long-term echosounder time series from the U.S. Ocean Observatories Initiative network

Building a toolbox for studying marine ecology using large ocean sonar datasets