How many dollars are in the sea? Estimating sand dollar (Echinarachnius parma) abundance using an iteratively trained convolutional neural network and generalized additive models

Details

• Journal Title:
  Ecological Informatics
• Personal Author:
  Vanaki, Sara ; Hart, Deborah R. ; Chang, Jui-Han
• NOAA Program & Office:
  NMFS (National Marine Fisheries Service) ; NEFSC (Northeast Fisheries Science Center)
• Description:
  The collection of imagery for population estimation is rapidly increasing. However, the number of images collected often exceeds the capacity to annotate these images manually. An alternative to human annotations is the use of computer vision to automatically count target organisms. Although the abilities of automated detectors has been considerably improving through the use of convolutional neural networks (CNNs), several obstacles remain before these detectors can be used for population estimates.
• Source:
  Ecological Informatics, 90, 103311
• DOI:
  https://doi.org/10.1016/j.ecoinf.2025.103311
• ISSN:
  1574-9541
• Format:
  pdf
• Publisher:
  Elsevier BV
• Document Type:
  Journal Article
• License:
  https://creativecommons.org/licenses/by-nc/4.0/
• Rights Information:
  CC BY-NC
• Compliance:
  Submitted
• Main Document Checksum:
  urn:sha-512:6501a80617679788a2d4b209052ba1b1d91fb1091fca0698cb9114851d8a311be27055140bc8ff49e7dac3a6193181e99793ded878e0a55943a5670e0cc6893a
• Download URL:
  https://repository.library.noaa.gov/view/noaa/72198/noaa_72198_DS1.pdf
• File Type:
  [PDF - 3.30 MB ]