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Dataset / Training image data for: Environmental and ecological drivers of harmful algal blooms …

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Title
Training image data for: Environmental and ecological drivers of harmful algal blooms in the Southern California Bight
Contributor
Carter, Melissa L.
Eggleston, Emily
Franks, Peter J.S.
Jaffe, Jules S.
Orenstein, Eric C.
Seech, Kristi
Shipe, Rebecca
Smith, Jayme
Date Created and/or Issued
2015 to 2019
Contributing Institution
UC San Diego, Research Data Curation Program
Collection
Training image data for: Environmental and ecological drivers of harmful algal blooms in the Southern California Bight
Rights Information
Under copyright
Constraint(s) on Use: This work is protected by the U.S. Copyright Law (Title 17, U.S.C.). Use of this work beyond that allowed by "fair use" or any license applied to this work requires written permission of the copyright holder(s). Responsibility for obtaining permissions and any use and distribution of this work rests exclusively with the user and not the UC San Diego Library. Inquiries can be made to the UC San Diego Library program having custody of the work.
Use: This work is available from the UC San Diego Library. This digital copy of the work is intended to support research, teaching, and private study.
Rights Holder and Contact
UC Regents
Description
The datasets include example images of marine protists and copepods that were used for training of machine classifiers in Kenitz et al. (in review). The images were collected by the Scripps Plankton Camera (SPC; http://spc.ucsd.edu/), located at the end of the Scripps Pier, La Jolla, CA, at the tide-dependent depth of approximately 3-4 m. The Scripps Plankton Camera system includes two free-space, darkfield microscopes: (i) micro-SPC equipped with a 5x objective for imaging of marine protists, and (ii) mini-SPC equipped with a 0.5x objective for imaging larger zooplankton. The images in this database were used for training of two distinct classifiers: 1) Multi-class classifier for classification of marine protists: Images for training of the multiclass classifier include examples of marine protists and other particles detected by the camera with the major axis in the range of 30-1000 microns. These images were collected by the micro-SPC. 2) Binary classifier for identification of marine copepods: Images for training of the binary classifier include example images of marine copepods and non-copepods with the major axis in the range of 1-5 mm. These images were collected by the mini-SPC. Example images for the non-copepod class include everything not specifically identified as a copepod, such as cladocerans, euphausiids, appendicularians, large diatom chains and other unidentifiable particles.
Simons Foundation National Science Foundation (NSF) BIGDATA Initiative (award #NSF IIS 15-46351)
Research Data Curation Program, UC San Diego, La Jolla, 92093-0175 (https://lib.ucsd.edu/rdcp)
Kenitz, Kasia M.; Anderson, Clarissa R.; Carter, Melissa L.; Eggleston, Emily; Seech, Kristi; Shipe, Rebecca; Smith, Jayme; Orenstein, Eric C.; Franks, Peter J.S.; Jaffe, Jules S.; Barton, Andrew D. (2022). Training image data for: Environmental and ecological drivers of harmful algal blooms in the Southern California Bight. UC San Diego Library Digital Collections. https://doi.org/10.6075/J00865GT
Type
dataset
Identifier
ark:/20775/bb3387869t
Language
No linguistic content
Subject
Scripps Plankton Camera, Scripps Pier
Algorithm: Supervised learning
Task: Feature extraction
Task: Binary classification
Underwater imaging
Training dataset
Machine learning
Plankton imaging
Task: Anomaly detection
Algorithm: Unsupervised learning
Algorithm: Semi-supervised learning
Task: Image classification
Task: Clustering
Task: Classification
Ellen Browning Scripps Memorial Pier (San Diego, Calif.)
Place
Ellen Browning Scripps Memorial Pier (San Diego, Calif.)

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