Assessing the Image Concept Drift at the OBSEA Coastal Underwater Cabled Observatory
13 pages, 9 figures, 2 tables.-- Data Availability Statement: The time series of specimen counts per species, obtained through the visual inspection of the image dataset, is provided as a supplementary material (only the images containing at least one specimen are reported). The image datasets analy...
| Autores: | , , , , , |
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| Tipo de documento: | artigo |
| Estado: | Versão publicada |
| Data de publicação: | 2022 |
| País: | España |
| Recursos: | Consejo Superior de Investigaciones Científicas (CSIC) |
| Repositório: | DIGITAL.CSIC. Repositorio Institucional del CSIC |
| OAI Identifier: | oai:digital.csic.es:10261/268712 |
| Acesso em linha: | http://hdl.handle.net/10261/268712 |
| Access Level: | Acceso aberto |
| Palavra-chave: | Concept drift Automated fish classification Automated fish detection Deep learning Underwater imaging Underwater observing systems Cabled observatories |
| Resumo: | 13 pages, 9 figures, 2 tables.-- Data Availability Statement: The time series of specimen counts per species, obtained through the visual inspection of the image dataset, is provided as a supplementary material (only the images containing at least one specimen are reported). The image datasets analysed for this study can be accessed by contacting the OBSEA observatory [https://www.obsea.es/] on reasonable request |
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