Unmanned Aerial Vehicle Imagery for Early Stage Weed Classification and Detection in Maize and Tomato Crops
[Description of methods used for collection/generation of data] Data were acquired through an RGB camera mounted on a UAV at an altitude of 11m. From the images obtained by the UAV, geomatic products were systematically generated for the creation of orthomosaics. This task was performed by incorporating information extracted from the RGB channels using Agisoft PhotoScan software (Agisoft LLC, St. Louis, MO). The resulting orthomosaics were subdivided into smaller sections. To identify and label weed species, malherbology experts carried out the task manually. This involved drawing bounding boxes around each plant and annotating various visible objects present in each divided image. This process was executed using the graphical tool labelImg open source software. The final result consists of a collection of individual images, each corresponding to a specific label, i.e., to each plant of each identified species.
| Main Authors: | , , , , , |
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| Other Authors: | |
| Format: | dataset biblioteca |
| Language: | English |
| Published: |
DIGITAL.CSIC
2024-02-19
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| Subjects: | UAV-imagery, Tomato, Weeds, Deep learning, Maize, |
| Online Access: | http://hdl.handle.net/10261/347533 |
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