DeepWeeds: A Multiclass Weed Species Image Dataset for Deep Learning

Robotic weed control has seen increased research of late with its potential for boosting productivity in agriculture. Majority of works focus on developing robotics for croplands, ignoring the weed management problems facing rangeland stock farmers. Perhaps the greatest obstacle to widespread uptake of robotic weed control is the robust classification of weed species in their natural environment. The unparalleled successes of deep learning make it an ideal candidate for recognising various weed species in the complex rangeland environment. This work contributes the first large, public, multiclass image dataset of weed species from the Australian rangelands; allowing for the development of robust classification…

• AG
  Australian Government
• DO
  Department of Agriculture, Australian Government

  Award: 4-53KULEI
• DO
  Department of Agriculture and Water Resources, Australian Government