Dr. Carolyn Binder - Machine Learning To Find Whales And Submarines In A Noisy Ocean Background

Passive and active sonar are the primary modalities to detect, classify, localize, and track (DCLT) objects in the ocean. Defence Research and Development Canada (DRDC) is researching machine learning methods to automate DCLT of underwater acoustic problems; ranging from using passive sonar to note the presence of whales to reduce risk of harm during active sonar exercises, to using active sonar for detection and tracking of ships and submarines. In most scenarios, machine learning methods must be applied in such a way to minimize false positives resulting from the noisy ocean background. This talk will focus on identifying requirements for state-of-the-art acoustic DCLT methods, particularly topics best-suited to the application of machine learning. Challenges in applying machine learning to ocean acoustic DCLT will be identified with the intent to stimulate thought and discussion on how to address these challenges. There are many opportunities for machine learning to demonstrate innovation and development of creative solutions to complex ocean acoustic problems.