Description
The CropAndWeed dataset is focused on the fine-grained identification of 74 relevant crop and weed species with a strong emphasis on data variability. Annotations of labeled bounding boxes, semantic masks and stem positions are provided for about 112k instances in more than 8k high-resolution images of both real-world agricultural sites and specifically cultivated outdoor plots of rare weed types. Additionally, each sample is enriched with meta-annotations regarding environmental conditions.
| Date made available | Jan 2023 |
|---|---|
| Date of data production | 2019 - 2022 |
Research Field
- Assistive and Autonomous Systems
Research output
- 1 Conference Proceedings with Oral Presentation
-
The CropAndWeed Dataset: A Multi-Modal Learning Approach for Efficient Crop and Weed Manipulation
Steininger, D. (Speaker), Trondl, A., Croonen, G., Simon, J. & Widhalm, V., 2023, Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision (WACV). 10 p.Research output: Chapter in Book or Conference Proceedings › Conference Proceedings with Oral Presentation › peer-review
Open Access
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