Testing the feasibility of deep learning approaches to enhance monitoring of marine macroinvertebrates: Insights from a case study using the gastropod Peringia ulvae.
- DOI
- 10.1007/s10661-026-15682-7
- Published
- 2026 Jul 14
- Container
- Environmental monitoring and assessment
- Publisher
- Not recorded
- Open access
- yes
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Cite this work
BibTeX
@article{allodium:10.1007/s10661-026-15682-7,
title = {Testing the feasibility of deep learning approaches to enhance monitoring of marine macroinvertebrates: Insights from a case study using the gastropod Peringia ulvae.},
author = {Jurado IC and Earp HS and Vanschoren J and Sugden H},
year = {2026},
journal = {Environmental monitoring and assessment},
doi = {10.1007/s10661-026-15682-7},
url = {https://doi.org/10.1007/s10661-026-15682-7}
}RIS
TY - JOUR TI - Testing the feasibility of deep learning approaches to enhance monitoring of marine macroinvertebrates: Insights from a case study using the gastropod Peringia ulvae. AU - Jurado IC AU - Earp HS AU - Vanschoren J AU - Sugden H PY - 2026 JO - Environmental monitoring and assessment DO - 10.1007/s10661-026-15682-7 UR - https://doi.org/10.1007/s10661-026-15682-7 ER -
APA
IC, J., HS, E., J, V., & H, S. (2026). Testing the feasibility of deep learning approaches to enhance monitoring of marine macroinvertebrates: Insights from a case study using the gastropod Peringia ulvae.. Environmental monitoring and assessment. https://doi.org/10.1007/s10661-026-15682-7
Source records
- pubmed · retrieved 2026-09-25T11:12:36.084Z