DeepSeagrass Dataset
Scarlett Raine, Ross Marchant, Peyman Moghadam, Frederic Maire, Brett, Kettle, Brano Kusy
TL;DR
This paper presents a new dataset of seagrass images from Moreton Bay, along with pre-trained models and code for species detection and classification, facilitating research in marine ecology and computer vision.
Contribution
It introduces a labeled seagrass image dataset and provides pre-trained models and code for species detection and classification.
Findings
Dataset enables improved seagrass species analysis.
Pre-trained models achieve accurate detection and classification.
Resource supports ecological and computer vision research.
Abstract
We introduce a dataset of seagrass images collected by a biologist snorkelling in Moreton Bay, Queensland, Australia, as described in our publication: arXiv:2009.09924. The images are labelled at the image-level by collecting images of the same morphotype in a folder hierarchy. We also release pre-trained models and training codes for detection and classification of seagrass species at the patch level at https://github.com/csiro-robotics/deepseagrass.
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Taxonomy
TopicsIdentification and Quantification in Food · Ichthyology and Marine Biology · Coral and Marine Ecosystems Studies