Machine Learning Acoustic Classification
We use machine learning algorithms to classify the undersea domain based on limited prior examples.
We accelerate and optimize decision-making through advanced analytics and machine learning algorithms deployed and integrated at the edge.
Triage acoustic data rather than rely on constant human monitoring.
Scale ASW operations to meet the emerging challenge.
Machine learning acoustic classification deployed to the edge with low SWaP and variable comms.
Earlier mechanical failure prediction lead-time through the automated discovery, extraction, and prediction of determinative spectral features.
Full-package flexibly-integrated solution with either stand-alone hardware-software package or API integration.
Prioritize Human Decision-making
Increase ASW Scale
Increase Readiness/ Availability
Lower Total Cost of Ownership
Improve Safety
We use machine learning algorithms to classify the undersea domain based on limited prior examples.
We use advanced causal machine learning algorithms to uncover the root causes of asset performance.
We use a Deep Reinforcement Learning solver to solve routing problems at scale, beyond the capability of traditional tools and without high performance computing.
We use machine learning algorithms to classify the undersea domain based on limited prior examples.
We use advanced causal machine learning algorithms to uncover the root causes of asset performance.
We use a Deep Reinforcement Learning solver to solve routing problems at scale, beyond the capability of traditional tools and without high performance computing.
Level 6, 74 Pirie Street Adelaide SA 5000 Australia
+61 429 455 406
