Underwater images and manual tags of different fish taxa detected from the image repository of the OBSEA Cabled Observatory from January 2013 to December 2014. OBSEA station is located 4km off-the-coast of Vilanova i la Geltrú (Catalonia, Spain) at a depth of 20 meters . Tags are rectangles marking the fish position in a picture (region of interest), identified by their x/y vertix values (in pixels).The aim of this dataset is to train Artificial Intelligence (AI) algorithms to automatically detect and or classify fish specimens from underwater pictures.Two cameras were used (Sony SNC-RZ25N from 2013-01-01 to 2014-12-11 and Axis P1346-E from 2014-12-11 to 2014-12-31). 29 fish taxa have been visually identified and classified according to the...
International audienceOne of the current challenges of marine ecology is to monitor biodiversity acc...
International audienceIn this paper we investigate the fine-grained object categorization problem of...
International audienceIn this paper, we address fish species identification in underwater video for ...
Underwater images and abundances of different fish taxa detected at the OBSEA Cabled Observatory fro...
Les progrès réalisés dans l’imagerie optique sous-marine conduisent de plus en plus à l’utilisation ...
Multiparametric video-cabled marine observatories are becoming strategic to monitor remotely and in ...
Cabled observatories offer new opportunities to monitor species abundances at frequencies and durati...
© International Council for the Exploration of the Sea 2017. All rights reserved. There is a need fo...
There is an urgent need for the development of sampling techniques which can provide accurate and pr...
Machine-assisted object detection and classification of fish species from Baited Remote Underwater V...
Advances in underwater optical imaging are increasingly leading to the use of these systems in surve...
12 pages, 5 figures, 4 tables, 1 video, supplementary material https://dx.doi.org/10.1038/s41598-018...
This dataset contains 1548 underwater images containing over 17965 labelled Mediterranean fish of 20...
Identifying and counting fish individuals on photos and videos is a crucial task to cost-effectively...
Underwater video and digital still cameras are rapidly being adopted by marine scientists and manage...
International audienceOne of the current challenges of marine ecology is to monitor biodiversity acc...
International audienceIn this paper we investigate the fine-grained object categorization problem of...
International audienceIn this paper, we address fish species identification in underwater video for ...
Underwater images and abundances of different fish taxa detected at the OBSEA Cabled Observatory fro...
Les progrès réalisés dans l’imagerie optique sous-marine conduisent de plus en plus à l’utilisation ...
Multiparametric video-cabled marine observatories are becoming strategic to monitor remotely and in ...
Cabled observatories offer new opportunities to monitor species abundances at frequencies and durati...
© International Council for the Exploration of the Sea 2017. All rights reserved. There is a need fo...
There is an urgent need for the development of sampling techniques which can provide accurate and pr...
Machine-assisted object detection and classification of fish species from Baited Remote Underwater V...
Advances in underwater optical imaging are increasingly leading to the use of these systems in surve...
12 pages, 5 figures, 4 tables, 1 video, supplementary material https://dx.doi.org/10.1038/s41598-018...
This dataset contains 1548 underwater images containing over 17965 labelled Mediterranean fish of 20...
Identifying and counting fish individuals on photos and videos is a crucial task to cost-effectively...
Underwater video and digital still cameras are rapidly being adopted by marine scientists and manage...
International audienceOne of the current challenges of marine ecology is to monitor biodiversity acc...
International audienceIn this paper we investigate the fine-grained object categorization problem of...
International audienceIn this paper, we address fish species identification in underwater video for ...