Deep machine learning provides state-of-the art performance in image-based plant phenotypingTools 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. and French, Andrew P. (2016) Deep machine learning provides state-of-the art performance in image-based plant phenotyping. Cold Spring Harbor Laboratory. Full text not available from this repository.
Official URL: http://biorxiv.org/content/early/2016/05/12/053033
AbstractDeep 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.
Actions (Archive Staff Only)
|
Tools
Tools
