Deep machine learning provides state-of-the art performance in image-based plant phenotyping - Pound, Michael P.; Burgess, Alexandra J.; Wilson, Michael H.; Atkinson, Jonathan A.; Griffiths, Marcus; Jackson, Aaron S.; Bulat, Adrian; Tzimiropoulos, Yorgos; Wells, Darren M.; Murchie, Erik H.; Pridmore, Tony P.; French, Andrew P. (Cold Spring Harbor Laboratory, 2016)
Deep learning is an emerging field that promises unparalleled results on many data analysis problems. We show the success offered by such techniques when applied to the challenging problem of image-based plant phenotyping, and demonstrate state-of-the-art results for root and shoot feature identification and localisation. We predict a paradigm shift in image-based phenotyping thanks to deep learning approaches.