Agricultural evolution with deep learning
Deep learning is pivotal in modern agriculture, especially for advanced agri-robots.
Using vast data, these robots discern patterns, optimising tasks from herbicide application to disease detection. However, their consistent performance hinges on a deep-learning system adept at agricultural complexities. This Mikroniek article explores challenges in crafting such systems, touching on economic impacts and design trade-offs. The AutoDL Platform is introduced, which is a solution for merging data & model management, task automation, and application insights. (Image courtesy of VBTI)