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Diabetes mellitus prediction and diagnosis from a data preprocessing and machine learning perspective (2022)
Journal Article
Olisah, C. C., Smith, L., & Smith, M. (2022). Diabetes mellitus prediction and diagnosis from a data preprocessing and machine learning perspective. Computer Methods and Programs in Biomedicine, 220, Article 106773. https://doi.org/10.1016/j.cmpb.2022.106773

Background and Objective: Diabetes mellitus is a metabolic disorder characterized by hyperglycemia, which results from the inadequacy of the body to secrete and respond to insulin. If not properly managed or diagnosed on time, diabetes can pose a ris... Read More about Diabetes mellitus prediction and diagnosis from a data preprocessing and machine learning perspective.

Precision fibre angle inspection for carbon fibre composite structures using polarisation vision (2021)
Journal Article
Atkinson, G., O'Hara Nash, S., & Smith, L. (2021). Precision fibre angle inspection for carbon fibre composite structures using polarisation vision. Electronics, 10(22), Article 2765. https://doi.org/10.3390/electronics10222765

This paper evaluates the precision of polarisation imaging technology for the inspection of carbon fibre composite components. Specifically, it assesses the feasibility of the technology for fibre orientation measurements based on the premise that li... Read More about Precision fibre angle inspection for carbon fibre composite structures using polarisation vision.

Towards facial expression recognition for on-farm welfare assessment in pigs (2021)
Journal Article
Hansen, M. F., Baxter, E. M., Rutherford, K. M. D., Futro, A., Smith, M. L., & Smith, L. N. (2021). Towards facial expression recognition for on-farm welfare assessment in pigs. Agriculture, 11(9), Article 847. https://doi.org/10.3390/agriculture11090847

Animal welfare is not only an ethically important consideration in good animal husbandry but can also have a significant effect on an animal’s productivity. The aim of this paper was to show that a reduction in animal welfare, in the form of increase... Read More about Towards facial expression recognition for on-farm welfare assessment in pigs.

The quiet revolution in machine vision - A state-of-the-art survey paper, including historical review, perspectives, and future directions (2021)
Journal Article
Smith, M. L., Smith, L. N., & Hansen, M. F. (2021). The quiet revolution in machine vision - A state-of-the-art survey paper, including historical review, perspectives, and future directions. Computers in Industry, 130, Article 103472. https://doi.org/10.1016/j.compind.2021.103472

Over the past few years, what might not unreasonably be described as a true revolution has taken place in the field of machine vision, radically altering the way many things had previously been done and offering new and exciting opportunities for tho... Read More about The quiet revolution in machine vision - A state-of-the-art survey paper, including historical review, perspectives, and future directions.

A computer vision approach to improving cattle digestive health by the monitoring of faecal samples (2020)
Journal Article
Atkinson, G. A., Smith, L. N., Smith, M. L., Reynolds, C. K., Humphries, D. J., Moorby, J. M., …Kingston-Smith, A. H. (2020). A computer vision approach to improving cattle digestive health by the monitoring of faecal samples. Scientific Reports, 10, Article 17557. https://doi.org/10.1038/s41598-020-74511-0

The digestive health of cows is one of the primary factors that determine their well-being and productivity. Under- and over-feeding are both commonplace in the beef and dairy industry; leading to welfare issues, negative environmental impacts, and e... Read More about A computer vision approach to improving cattle digestive health by the monitoring of faecal samples.

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.

Visual features based boosted classification of weeds for real-time selective herbicide sprayer systems (2018)
Journal Article
Jamil, A., Khan, M., Imran, A., Wakeel, A., Smith, M., Smith, L., …Irfan, M. (2018). Visual features based boosted classification of weeds for real-time selective herbicide sprayer systems. Computers in Industry, 98, 23-33. https://doi.org/10.1016/j.compind.2018.02.005

© 2018 Recent years have shown enthusiastic research interest in weed classification for selective herbicide sprayer systems which are helpful in eradicating unwanted plants such as weeds from fields, minimizing the side effects of chemicals on the e... Read More about Visual features based boosted classification of weeds for real-time selective herbicide sprayer systems.

Towards on-farm pig face recognition using convolutional neural networks (2018)
Journal Article
Baxter, E. M., Salter, M. G., Smith, L. N., Smith, M. L., Hansen, M. F., Hansen, M. F., …Grieve, B. (2018). Towards on-farm pig face recognition using convolutional neural networks. Computers in Industry, 98, 145-152. https://doi.org/10.1016/j.compind.2018.02.016

© 2018 Elsevier B.V. Identification of individual livestock such as pigs and cows has become a pressing issue in recent years as intensification practices continue to be adopted and precise objective measurements are required (e.g. weight). Current b... Read More about Towards on-farm pig face recognition using convolutional neural networks.