Confluence Retirement

Due to the feedback from stakeholders and our commitment to not adversely impact USGS science activities that Confluence supports, we are extending the migration deadline to January 2023.

In an effort to consolidate USGS hosted Wikis, myUSGS’ Confluence service is targeted for retirement. The official USGS Wiki and collaboration space is now SharePoint. Please migrate existing spaces and content to the SharePoint platform and remove it from Confluence at your earliest convenience. If you need any additional information or have any concerns about this change, please contact myusgs@usgs.gov. Thank you for your prompt attention to this matter.

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Abstract: This presentation provides an overview of how we use a recurrent autoencoder neural network to encode sequential Californiagolden California golden eagle telemetry data. The encoding is followed by an unsupervisedclustering unsupervised clustering technique, Deep Embedded Clustering (DEC), to iteratively clusterthe cluster the data into a chosen number of behavior classes. We apply the method tosimulated to simulated movement data sets and telemetry data for a Golden Eagle. The DECachieves better unsupervised clustering accuracy scores for the simulated datasets as compared to the baseline K-means clustering result.

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