Artificial Intelligence Tools for Agriculture
Weeds are one of the biggest agricultural challenges; they compete with crops for available nutrients, water, and sunlight. Myriad approaches, most notably RGB sensors, have been used to identify and map weeds using computer vision. For instance, a simple string weeder (aka a “weed eater”) paired with a camera can control very small weeds with unprotected growing points. As weeds get larger and more invasive, more expensive methods may be necessary, and some success has been had with robot-mounted lasers. The OpenCV AI Kit with Depth (OAK-D) by OpenCV a computer vision project is pushing the dimensions of AI in agriculture.
In this tutorial, Deep Stack researchers show how you can use Artificial Intelligence through the use of computer vision and deep learning to automate bad or good produce detection, sorting and identification of damaged ones and hence can improve produce management for many African food packers reducing waste and increasing productivity and profit.
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