Label the data needed for your agricultural AI with a Human in the Loop!
Labeling for AgriTech is not an easy task, because it requires annotators to develop a very deep expertise in the types of plants they are dealing with. Our teams have a proven track record of working with companies and research institutes and producing high-quality labeling on both RGB and multispectral imagery.
Client success story
Read how French research institute InRAE has partnered with Humans in the Loop in order to use annotation to optimize the plant phenotyping process
Precision agriculture needs a lot of data about plant growth stage and yield in order to apply water and fertilizer in a targeted way. This requires the labeling of each crop with information about its growth stage and status (e.g. water stress, nitrogen stress, etc).
With labeled data, often aerial and sometimes even satellite images, computer vision models can be trained to classify the soil in an area. This can be useful for example in searching for fertile land, or tracking the effects of deforestation and erosion.
Download our free plant segmentation dataset!
Humans in the Loop has published an open access segmentation masks for a dataset provided by the Computer Vision and Biosystems Signal Processing Group at the Department of Electrical and Computer Engineering at Aarhus University
Types of annotation
Interested in having a Human in the Loop label your Agriculture dataset?
Get in touch with our team at Humans in the Loop and a project manager will help you find the best solution to your computer vision needs!