Summary of Eurocropsml: a Time Series Benchmark Dataset For Few-shot Crop Type Classification, by Joana Reuss et al.
EuroCropsML: A Time Series Benchmark Dataset For Few-Shot Crop Type Classification
by Joana Reuss, Jan Macdonald, Simon Becker, Lorenz Richter, Marco Körner
First submitted to arxiv on: 24 Jul 2024
Categories
- Main: Machine Learning (cs.LG)
- Secondary: None
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| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary This research introduces EuroCropsML, a dataset designed to evaluate machine learning algorithms for classifying crop types in agricultural parcels across Europe. The dataset comprises 706,683 labeled data points spanning 176 classes, featuring time-series pixel values from Sentinel-2 satellite imagery and spatial coordinates. It is the first benchmarking dataset for few-shot crop type classification, supporting advancements in algorithm development and research comparability. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary EuroCropsML is a new dataset that helps scientists develop better computer programs to identify different types of crops growing in fields across Europe. The dataset has over 700,000 examples, each with information about the crop type and location. It’s like a big puzzle that researchers can use to test their ideas and see which ones work best. |
Keywords
» Artificial intelligence » Classification » Few shot » Machine learning » Time series
