Browsing by Author "Fortson, Lucy"

Now showing 1 - 3 of 3
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    Camera Trap Images used in "Identifying Animal Species in Camera Trap Images using Deep Learning and Citizen Science"
    (2018-08-28) Willi, Marco; Pitman, Ross T; Cardoso, Anabelle W; Locke, Christina; Swanson, Alexandra; Boyer, Amy; Veldthuis, Marten; Fortson, Lucy; will5448@umn.edu; Willi, Marco; University of Minnesota - School of Physics and Astronomy; University of Minnesota - Data Science MS program
    This dataset provides the camera trap images used in "Identifying Animal Species in Camera Trap Images using Deep Learning and Citizen Science" as well as meta-data about the images. The Snapshop Serengeti collection includes 6,163,870 images in JPG format. The Snapshot Wisconsin collection includes 497,204 images in JPG format. The Camera CATalogue collection include 506,241 images in JPG format. Excluded are the images for the dataset "Elephant Expedition" which will be published separately outside DRUM. Also excluded are images of humans due to privacy reasons.
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    Software, Data & Models used in "Identifying Animal Species in Camera Trap Images using Deep Learning and Citizen Science"
    (2018-08-28) Willi, Marco; Pitman, Ross T; Cardoso, Anabelle W; Locke, Christina; Swanson, Alexandra; Boyer, Amy; Veldthuis, Marten; Fortson, Lucy; will5448@umn.edu; Willi, Marco; University of Minnesota - School of Physics and Astronomy; University of Minnesota - Data Science MS program
    This dataset provides the software, the models, and other data used in "Identifying Animal Species in Camera Trap Images using Deep Learning and Citizen Science". This dataset contains the software to train convolutional neural networks, as well as all models trained for the study and code to apply them on new images. Additionally, data defining the conducted experiments are provided to ensure reproducibility.
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    Solar Jet Hunter: Jet Catalog from HEK Events 2011-2016
    (2023-09-25) Musset, Sophie; Sankar, Ramanakumar; Lasko, Kekoa; Jol, Paloma; Glesener, Lindsay; Fleishman, Gregory; Panesar, Navdeep; Zhang, Yixian; Hurlburt, Neal; Fortson, Lucy; Ostlund, Erik; Alnahari, Suhail; Jeunon, Mariana; Kapsiak, Charles; glesener@umn.edu; Glesener, Lindsay; UMN Space Physics Group
    This database constitutes the first release of data from the Solar Jet Hunter project. Solar Jet Hunter is a Zooniverse-based citizen science project that has, since 2021, enlisted volunteers from the general public to help identify extreme ultraviolet jets of plasma in the Sun’s corona. These jets release magnetic energy at the Sun and enable streams of plasma and energetic particles to escape to the solar system, but the origins of and mechanisms underlying these jets are still not understood. In Solar Jet Hunter, videos of possible jets are presented to volunteers, who are asked to identify whether a jet is present, and if so, its start time, end time, and base location. Volunteers also box the jet, providing information on its shape and height over time. The results from many volunteers are then aggregated into consensus results for each potential jet in the study. Those results are listed in this data set. The data presented to volunteers is from the Solar Dynamic Observatory / Atmospheric Imaging Assembly instrument, specifically the 304 angstrom filter, and all of the candidate jets were identified as possible jets in the Heliophysics Event Knowledgebase (HEK). The data set included here lists Solar Jet Hunter results from the years 2011 through 2016.