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Dataset

WeedMap

Potential Application: Identification and segmentation of crops and weeds
high resolution NIR UAV image detection identification weeds semantic segmentation
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Description

The dataset consists of multispectral ortho mosaic images covering 16,550m2 sugar beet fields collected by five-band RedEdge-M and four-band Sequoia cameras in Rheinbach (Germany) and Eschikon (Switzerland). The spatiotemporal datasets contain high-resolution multispectral sugar beet/weed images with expert labeling.

Biological Information
  • Species: Sugar beet
  • Latin name: Beta vulgaris
  • Imaging tissue: Shoot
    • Function Information
  • Computer vision tasks: Image detection
  • Potential application: Identification and segmentation of crops and weeds
  • Labeled instances: 5017
  • Label type: Semantic segmentation
  • Related traits: -
    • Imaging
  • Total number of images: 18736
  • Image format: PNG
  • Average resolution: 507×388
  • Sensors: NIR (near infrared)
  • Dataset size: 4.2G
  • Sampling geographic location: Switzerland; Germany
  • Acquisition equipment: Five-band RedEdge-M and four-band Sequoia cameras in Rheinbach (Germany) and Eschikon (Switzerland)
  • Sampling platform: UAV (unmanned aerial vehicle)
    • Citation
    90+ images in total    2/2