Alex Witsil-Thesis Defense

Quantifying and Classifying Volcano Video and Infrasound Datasets via Computer Vision and Machine Learning Algorithms

Volcanoes are dangerous and complex with processes coupled to both the subsurface and atmosphere. Effective monitoring of volcanic behavior during and in between periods of crisis requires a diverse suite of instruments and processing routines. Acoustic microphones and video cameras are typical in long-term deployments and provide important constraints on surficial and observational activity yet are underutilized relative to their seismic counterpart. This thesis increases the utility of infrasound and video datasets through novel applications of computer vision and machine learning algorithms, which help constrain source dynamics and track shifts in activity.

Where: RUCH 103
When: Wednesday, February 19th
Time: 3:00p.m.
Directions: Map