All Outputs (3)

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.

Weed classification in grasslands using convolutional neural networks (2019)
Conference Proceeding
Smith, L. N., Byrne, A., Hansen, M. F., Zhang, W., & Smith, M. L. (2019). Weed classification in grasslands using convolutional neural networks. . https://doi.org/10.1117/12.2530092

Automatic identification and selective spraying of weeds (such as dock) in grass can provide very significant long-term ecological and cost benefits. Although machine vision (with interface to suitable automation) provides an effective means of achie... Read More about Weed classification in grasslands using convolutional neural networks.

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.