EDIS Spotlight: Applications of Artificial Intelligence for Precision Agriculture

Real-time citrus detection using YOLO (a real-time AI object detection algorithm) on an NVidia Jetson TX2 board (Graphics Processing Unit, GPU). These results are achieved by using just 150 pictures to train the AI-based system.
Credit: UF/IFAS

Technology advances have enabled the development and implementation of remote sensing technologies for plant, weed, pest, and disease identification and management. This provides an opportunity to develop intelligent agricultural systems for precision applications using artificial intelligence and machine learning.

In this Electronic Data Information Source (EDIS) publication, Yiannis Ampatzidis, agricultural and biological engineering assistant professor and precision agriculture researcher, discusses artificial intelligence (AI) and machine learning concepts and explains how AI can be applied in agriculture through object, disease, and pest detection.

Visit the EDIS website to read more from this publication or download a printable PDF version. Read more from the UF/IFAS Agricultural and Biological Engineering department on our blog.

Follow UF/IFAS Agricultural and Biological Engineering on Twitter, Facebook, and Instagram. Follow Yiannis Ampatzidis and the SWFREC Precision Agriculture Lab on Twitter.


Posted: March 23, 2020

Category: Agriculture, Crops, Farm Management, Pests & Disease, UF/IFAS, UF/IFAS, UF/IFAS Extension, UF/IFAS Research
Tags: Agricultural And Biological Engineering, Agriculture, AI, Artificial Intelligence, Disease Detection, EDIS, Machine Learning, Pest Detection, Precision Agriculture, Research, SWFREC, Yiannis Ampatzidis

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