This dataset is supporting the University of Southampton Doctoral Thesis "Detection and segmentation of fauna in seafloor imagery for biomass estimation". The dataset includes: FK2018 Coco Format Labelled Images. The images were taken from AE2000f and Tuna sand labelled with 5 morphotypes in the coco segment format, Crabs, Hagfish, Flatfish, Sea Stars, and Rockfish. The data is stored on Zenodo at https://doi.org/10.5281/zenodo.8335053 Under the CC BY license</span
Schoening T, Purser A, Langenkämper D, et al. Megafauna community assessment of polymetallic-nodule ...
Dataset: Core samples: Infauna abundanceInfauna abundance from seagrass bed core samples collected i...
In this data set, we provide environmental (coordinates, depth, temperature, salinity, type of subst...
The performance of automated object detection and segmentation in marine imaging applications is sen...
Dataset: SMURF faunal settlementCollections of fish and invertebrates settles in artificial seagrass...
Here we present a technique for automatic classification of seafloor data collected during the 2012 ...
Underwater imagery is widely used for a variety of applications in marine biology and environmental ...
Abstract- This paper reports on a methodology developed for the analysis of near-bottom photographs ...
Dataset: Core samples: Infauna biomassInfauna biomass from seagrass bed core samples collected in Ba...
Data Study Groups are week-long events at The Alan Turing Institute bringing together some of the co...
This dataset is a test dataset of image patches created from the 'novel-test' split of the Global We...
A comprehensive seafloor biomass and abundance database has been constructed from 24 oceanographic i...
Dataset: Fauna on restored oyster reefsThis dataset contains results from experiments comparing reef...
Manual analysis of large amounts of benthic images is time consuming and costly. This challenge has ...
Imagery collected by still and video cameras is an increasingly important tool for minimal impact, r...
Schoening T, Purser A, Langenkämper D, et al. Megafauna community assessment of polymetallic-nodule ...
Dataset: Core samples: Infauna abundanceInfauna abundance from seagrass bed core samples collected i...
In this data set, we provide environmental (coordinates, depth, temperature, salinity, type of subst...
The performance of automated object detection and segmentation in marine imaging applications is sen...
Dataset: SMURF faunal settlementCollections of fish and invertebrates settles in artificial seagrass...
Here we present a technique for automatic classification of seafloor data collected during the 2012 ...
Underwater imagery is widely used for a variety of applications in marine biology and environmental ...
Abstract- This paper reports on a methodology developed for the analysis of near-bottom photographs ...
Dataset: Core samples: Infauna biomassInfauna biomass from seagrass bed core samples collected in Ba...
Data Study Groups are week-long events at The Alan Turing Institute bringing together some of the co...
This dataset is a test dataset of image patches created from the 'novel-test' split of the Global We...
A comprehensive seafloor biomass and abundance database has been constructed from 24 oceanographic i...
Dataset: Fauna on restored oyster reefsThis dataset contains results from experiments comparing reef...
Manual analysis of large amounts of benthic images is time consuming and costly. This challenge has ...
Imagery collected by still and video cameras is an increasingly important tool for minimal impact, r...
Schoening T, Purser A, Langenkämper D, et al. Megafauna community assessment of polymetallic-nodule ...
Dataset: Core samples: Infauna abundanceInfauna abundance from seagrass bed core samples collected i...
In this data set, we provide environmental (coordinates, depth, temperature, salinity, type of subst...