Manuel González-Rivero, Alberto Rodriguez-Ramirez, Oscar Beijbom, P. Dalton, E. Kennedy, B. Neal, Julie Vercelloni, P. Bongaerts, A. Ganase, Dominic E. P. Bryant, K. Brown, Catherine J. S. Kim, Veronica Z. Radice, S. Lopez‐Marcano, S. Dove, C. Bailhache, H. Beyer, O. Hoegh‐Guldberg
{"title":"Seaview Survey Photo-quadrat and Image Classification Dataset","authors":"Manuel González-Rivero, Alberto Rodriguez-Ramirez, Oscar Beijbom, P. Dalton, E. Kennedy, B. Neal, Julie Vercelloni, P. Bongaerts, A. Ganase, Dominic E. P. Bryant, K. Brown, Catherine J. S. Kim, Veronica Z. Radice, S. Lopez‐Marcano, S. Dove, C. Bailhache, H. Beyer, O. Hoegh‐Guldberg","doi":"10.14264/uql.2019.930","DOIUrl":null,"url":null,"abstract":"The primary scientific dataset arising from the XL Catlin Seaview Survey project is the “Seaview Survey Photo-quadrat and Image Classification Dataset”, consisting of: (1) over one million standardised, downward-facing “photo-quadrat” images covering approximately 1m2 of the sea floor; (2) human-classified annotations that can be used to train and validate image classifiers; and (3) benthic cover data arising from the application of machine learning classifiers to the photo-quadrats. Photo-quadrats were collected between 2012 and 2018 at 860 transect locations around the world, including: the Caribbean and Bermuda, the Indian Ocean (Maldives, Chagos Archipelago), the Coral Triangle (Indonesia, Philippines, Timor-Leste, Solomon Islands), the Great Barrier Reef, Taiwan and Hawaii. For additional information regarding methodology, data structure, organization and size, please see attached document “Dataset documentation”.","PeriodicalId":243136,"journal":{"name":"UQ eSpace","volume":"106 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"UQ eSpace","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.14264/uql.2019.930","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 4
Abstract
The primary scientific dataset arising from the XL Catlin Seaview Survey project is the “Seaview Survey Photo-quadrat and Image Classification Dataset”, consisting of: (1) over one million standardised, downward-facing “photo-quadrat” images covering approximately 1m2 of the sea floor; (2) human-classified annotations that can be used to train and validate image classifiers; and (3) benthic cover data arising from the application of machine learning classifiers to the photo-quadrats. Photo-quadrats were collected between 2012 and 2018 at 860 transect locations around the world, including: the Caribbean and Bermuda, the Indian Ocean (Maldives, Chagos Archipelago), the Coral Triangle (Indonesia, Philippines, Timor-Leste, Solomon Islands), the Great Barrier Reef, Taiwan and Hawaii. For additional information regarding methodology, data structure, organization and size, please see attached document “Dataset documentation”.
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