A photometric stereo-based 3D imaging system using computer vision and deep learning for tracking plant growth

Bernotas, Gytis; Scorza, Livia C.T.; Hansen, Mark F.; Hales, Ian J.; Halliday, Karen J.; Smith, Lyndon N.; Smith, Melvyn L.; McCormick, Alistair J.

doi:10.1093/gigascience/giz056

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Understanding unconventional preprocessors in deep convolutional neural networks for face identification (2019)
Journal Article
Olisah, C. C., & Smith, L. (2019). Understanding unconventional preprocessors in deep convolutional neural networks for face identification. SN Applied Sciences, 1(11), https://doi.org/10.1007/s42452-019-1538-5

Deep convolutional neural networks have achieved huge successes in application domains like object and face recognition. The performance gain is attributed to different facets of the network architecture such as: depth of the convolutional layers, ac... Read More about Understanding unconventional preprocessors in deep convolutional neural networks for face identification.

A photometric stereo-based 3D imaging system using computer vision and deep learning for tracking plant growth (2019)
Journal Article
Bernotas, G., Scorza, L. C., Hansen, M. F., Hales, I. J., Halliday, K. J., Smith, L. N., …McCormick, A. J. (2019). A photometric stereo-based 3D imaging system using computer vision and deep learning for tracking plant growth. GigaScience, 8(5), Article giz056. https://doi.org/10.1093/gigascience/giz056

© The Author(s) 2019. Published by Oxford University Press. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distri... Read More about A photometric stereo-based 3D imaging system using computer vision and deep learning for tracking plant growth.