Datasets › Lincolnbeet
Lincolnbeet
The Lincolnbeet dataset is an object detection dataset designed to encourage research in the identification of items in environments with high levels of occlusion, and in the development of better approaches to evaluate object detection models in practical scenarios. This dataset was introduced in the paper: "Towards practical object detection for weed spraying in precision agriculture".
The dataset contains 4402 images that contain weed plants and sugar beets which are located with object detection labels. The image size is 1920 x 1080 pixels, and the labels included in the dataset are in COCOjson, XML, and darknets formats.
Benchmarks archive 2025-07-28
No leaderboard in the archive resolves to this dataset.
Papers archive 2025-07-28
No paper in the archive has a leaderboard row on this dataset; the archive counts 1 paper for it but never published that list.
Dataset loaders archive 2025-07-28
1 loader as listed in the archive; links are outbound and not re-checked here.
Tasks archive 2025-07-28
No task tagged in the archive.
License archive 2025-07-28
GPL
Modalities archive 2025-07-28
Languages archive 2025-07-28
Variants archive 2025-07-28
- Lincolnbeet
1 variant name, as the archive lists them.
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