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Template Matching to Identify Features in Vertical Profiles, or TMIFVP, is a tool designed to match and quantify the difference between a template profile and user-submitted data, clearly highlighting features for quality matching scores and location of problematic or interesting attributes. More broadly, this pipeline could be used to analyze and compare many types of graphs and profiles, including but not limited to: Michaelis-Menten population curves, Metabolomic and proteomic spectrographic peaks, and environmental time series data to identify outliers.
This project allows Python beginners a way to easily link and visualize animal movement data with sensed oceanographic data and databases of mesoscale oceanographic features.
Called, "a Semi Supervised Annotation Tool: Kickass AI to count sand dollars", the Underwater Currency Counter is an effort to train a deep object recognition algorithm to count sand dollars from benthic habitat imagery data collected from ROVs.
This team aims to provide a way to Co-locate oceanographic data by establishing constraints. The tools they developed allow users to provide geospacial bounds in a temporal range to get an aggregated response of all available data.
### Project: Modeling Volcano Deformation at Axial Seamount
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A Jupyter notebook intended to teach and demonstrate to undergraduates about volcano and seafloor deformation, and how previous volcanic eruptions of Axial Seamount were used to forecast future eruptions. This notebook also allows students to forecast the next eruption themselves!
The objective is to create an interface that allows to visualize the spectrogram and waveform of the fish sounds detected as well as the video and sonar data at the time of the detection.
### Project: Working with Chlorophyll Data from the Cloud
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Notebooks demonstrating how to work with chlorophyll data including how to remotely access chlorophyll data from OceanData.sci, how to read the data, and how to compute local gradients in the measured values.
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