Data-Centric Zero-Shot Learning for Precision Agriculture with Dimitris Zermas - #615

Today we’re joined by Dimitris Zermas, a principal scientist at agriscience company Sentera. Dimitris’ work at Sentera is focused on developing tools for precision agriculture using machine learning, including hardware like cameras and sensors, as well as ML models for analyzing the vast amount of data they acquire. We explore some specific use cases for machine learning, including plant counting, the challenges of working with classical computer vision techniques, database management, and data annotation. We also discuss their use of …

agriculture annotation cameras cases challenges computer computer vision data data annotation database database management data-centric discuss hardware machine machine learning management ml models precision sensors tools use cases vision work