Update README.md

README.md

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 pretty_name: 'JAMBO, A Multi-Annotator Image Dataset for Benthic Habitat Classification '
 size_categories:
 - 1K<n<10K
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+---
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+The JAMBO dataset contains underwater images of the seabed captured by an ROV in temperate waters in the Jammer Bay area off the North West coast of Jutland, Denmark.
+All the images have been annotated by six annotators to contain one of three classes: sand, stone, or bad. The three classes are defined as follows:
+* **Sand** habitats are characterized as primarily sand or muddy sand with less than 5% clay and less than 30% cover of stones/boulders, vegetation, and mussel bed.
+* **Stone** reef habitats are characterized by having more than 30% seabed cover of stones or boulders.
+* **Bad** is a class used to label images that cannot be confidently annotated as containing one of the aforementioned habitat types by the annotator due to poor image quality, turbidity, or similar.
+
+Each of the six annotators have labelled all the images, which allows for analyzing how inter-annotator disagreement can affect the performance of machine learning models.
+
+For more information, please see the paper to be presented the ECCV 2024 Computer Vision for Ecology (CV4E) Workshop.