Agriculture is facing a number of challenges—an increase in the demand for food and food safety, decreasing agricultural land, and labor shortages among them.
Computer vision applications powered by complex Machine Learning (ML) algorithms are helping to address many of these challenges by automating tasks—from crop monitoring and weed control to livestock health and supply chain optimization.
In this e-book we’ll cover:
How Precision Agriculture is improving productivity & yield
- Crop management & weed detection
- Crop sorting & quality assurance
- Food supply chain management
Top challenges AgTech models face & what to do about them
- High variability of crop, pest and disease data
- Poor image and video quality from drones or cameras
- Lack of visibility into model performance & drift