Deep Learning for Computational Agriculture & Phenomics
I lead the Deep Learning for Phenomics flagship project of the Plant Phenotyping and Imaging Research Center (P2IRC) at the University of Saskatchewan. We are working to lead the world in deep learning methods applied to phenomics in plant breeding. We are actively translating these approaches to broader applications in computational agriculture together with industry partners.
This project part of the $37M Canada First Research Excellence Fund grant to the Global Institute for Food Security (GIFS). Research activities include computer vision, deep learning, and modeling of plant health, development and response-to-stress.
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Crop Imaging and Datasets
We are also developing new ways to capture images of crops in the field, in order to generate rich datasets combining images, phenotypic measurements, and genomic information for a range of plant species.
