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  4. Data used to test a video monitoring and computational system for estimating juvenile fish abundance

Data used to test a video monitoring and computational system for estimating juvenile fish abundance

Dates

Publication Date
Start Date
2017-06-01
End Date
2017-11-30

Citation

Marjadi, M.N., Roy, A.H., Llopiz, J.K., and Sheppard, J. 2023. Data used to test a video monitoring and computational system for estimating juvenile fish abundance: U.S. Geological Survey data release, https://doi.org/10.5066/P93XRINQ.

Summary

We developed and tested neural network-based models to recognize and count emigrating juvenile river herring in continuous video. Continuous video was collected from an underwater camera installed at Great Herring Pond in Bourne, Massachusetts (USA) between June and November 2017. Our algorithm extracts video frames to assess presence/absence of fish and count numbers of fish emigrating. We used extracted video frames to assess model performance. Provided datasets include information about extracted frames that were used for model assessment. This data release includes four datasets that were used to test model performance and select the best fitting model. (1) The “Model Evaluation Dataset” includes count and presence/absence classifications [...]

Contacts

Point of Contact :
Allison Roy
Originator :
Meghna N. Marjadi, Allison Roy, Joel K. Llopiz, John Sheppard
Metadata Contact :
Meghna N. Marjadi
Publisher :
U.S. Geological Survey
Distributor :
U.S. Geological Survey - ScienceBase
SDC Data Owner :
Cooperative Research Units
USGS Mission Area :
Ecosystems

Attached Files

Click on title to download individual files attached to this item.

2023_07_25_emigration_methods_metadata.xml
Original FGDC Metadata
View 		66.53 KB application/fgdc+xml
2023_06_01_count_evaluation_data.csv 18.64 KB text/csv
2023_06_01_expert_validation_dataset_new.csv 3.55 KB text/csv
2023_06_01_model_evaluation_data.csv 3.46 MB text/csv
2023_06_01_volunteer_validation_dataset_new.csv 427.9 KB text/csv

Purpose

We collected continuous video data and extracted video frames to assess accuracy of a neural network at a counting fish in frames. These data could be used to confirm our assessments of the methods we evaluated.

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Communities

  • Cooperative Fish and Wildlife Research Units
  • USGS Data Release Products

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Identifiers

Type Scheme Key
DOI https://www.sciencebase.gov/vocab/category/item/identifier doi:10.5066/P93XRINQ

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