Omkar2118/datasets huggingface dataset:
MARIDA
Full name: Marine Debris Archive

**MARIDA** (**Marine Debris Archive**) is the first dataset based on the multispectral Sentinel-2 (S2) satellite data, which distinguishes Marine Debris from various marine features that co-exist, including Sargassum macroalgae, Ships, Natural Organic Material, Waves, Wakes, Foam, dissimilar water types (i.e., Clear, Turbid Water, Sediment-Laden Water, Shallow Water), and Clouds. MARIDA is an open-access dataset which enables the research community to explore the spectral behaviour of certain floating materials, sea state features and water types, to develop and evaluate Marine Debris detection solutions based on artificial intelligence and deep learning architectures, as well as satellite pre-processing pipelines.  Although it is designed to be beneficial for several machine learning tasks, it primarily aims to benchmark weakly supervised pixel-level semantic segmentation learning methods. 

MARIDA can be downloaded from the repository Zenodo ([https://doi.org/10.5281/zenodo.5151941](https://zenodo.org/record/5151941#.YfFZ_PXP30o)). A quick start guide for all ML benchmarks and the detailed overview of the dataset are available at [https://marine-debris.github.io/](https://marine-debris.github.io/).

Introducing paper: MARIDA: A benchmark for Marine Debris detection from Sentinel-2 remote sensing data
A ground-truth dataset to identify bots in GitHub

This dataset is a ground truth dataset that is used to identify bots. Each account in this dataset is rated by at least 3 raters with a high interrater agreement.

Introducing paper: A ground-truth dataset and classification model for detecting bots in GitHub issue and PR comments