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All Outputs (63)

3D Machine vision and deep learning for enabling automated and sustainable assistive physiotherapy (2023)
Conference Proceeding
Smith, L., Boyd, S., Bhatta, D., & Smith, M. (in press). 3D Machine vision and deep learning for enabling automated and sustainable assistive physiotherapy.

The significant beneficial effects of physiotherapy as a treatment for a wide range of medical conditions, is well known. However, the challenge for already stressed healthcare systems to provide effective physiotherapy to an aging population, that h... Read More about 3D Machine vision and deep learning for enabling automated and sustainable assistive physiotherapy.

Maize yield predictive models and mobile-based decision support system for smallholder farmers in Africa (2022)
Presentation / Conference
Olisah, C., Smith, L. N., & Smith, M. L. (2022, July). Maize yield predictive models and mobile-based decision support system for smallholder farmers in Africa. Paper presented at 17th International Conference on Machine Learning and Data Mining MLDM 2022, New York, USA

Existing machine learning models for crop yield prediction model environmental data on the assumption that soil variables are unaffected by weather variables and therefore learn their intrinsic features independently. If the focus of crop yield predi... Read More about Maize yield predictive models and mobile-based decision support system for smallholder farmers in Africa.

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.

A robust machine learning framework for diabetes prediction (2021)
Conference Proceeding
Olisah, C., Adeleye, O., Smith, L., & Smith, M. (2022). A robust machine learning framework for diabetes prediction. In Proceedings of the Future Technologies Conference (FTC) 2021 (775-792). https://doi.org/10.1007/978-3-030-89880-9_58

Diabetes mellitus is a metabolic disorder characterized by hyperglycemia which results from the inadequacy of the body to secret and responds to insulin. If not properly managed or diagnosed on time, diabetes can pose a risk to vital body organs such... Read More about A robust machine learning framework for diabetes prediction.

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.

Contactless robust 3D palm-print identification using photometric stereo (2021)
Conference Proceeding
Smith, L. N., Langhof, M. P., Hansen, M. F., & Smith, M. L. (2021). Contactless robust 3D palm-print identification using photometric stereo. https://doi.org/10.1117/12.2595439

Palmprints are of considerable interest as a reliable biometric, since they offer significant advantages, such as greater user acceptance than fingerprint or iris recognition. 2D systems can be spoofed by a photograph of a hand; however, 3D avoids th... Read More about Contactless robust 3D palm-print identification using photometric stereo.

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.

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.

Broad-leaf weed detection in pasture (2018)
Conference Proceeding
Zhang, W., Hansen, M. F., Volonakis, T. N., Smith, M., Smith, L., Wilson, J., …Wright, G. (2018). Broad-leaf weed detection in pasture.

Weed control in pasture is a challenging problem that can be expensive and environmentally unfriendly. This paper proposes a novel method for recognition of broad-leaf weeds in pasture such that precision weed control can be achieved with reduced her... Read More about Broad-leaf weed detection in pasture.

Multispectral contactless 3D handprint acquisition for identification (2018)
Presentation / Conference
Hansen, M. F., Smith, L., & Smith, M. (2018, July). Multispectral contactless 3D handprint acquisition for identification. Paper presented at The 20th International Conference on Artificial Intelligence, 2018 World Congress in Computer Science, Computer Engineering, & Applied Computing, Las Vegas, USA

We present and experimentally demonstrate the potential effectiveness of a photometric stereo based high resolution system for capturing 3D handprints using visible light sources. The sub-surface vascular structures are also enhanced through the use... Read More about Multispectral contactless 3D handprint acquisition for identification.

2D and 3D face analysis for ticketless rail travel (2018)
Conference Proceeding
Smith, L., Zhang, W., & Smith, M. L. (2018). 2D and 3D face analysis for ticketless rail travel. In Proceedings of the 2018 International Conference on Image Processing, Computer Vision, & Pattern Recognition. , (16-22)

Research is reported into the design, implementation and functionalities of a vision system that employs the human face as a biometric for enabling ticketless rail travel. The system has been developed to optimise performance in the relatively unstru... Read More about 2D and 3D face analysis for ticketless rail travel.

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.

Innovative 3D and 2D machine vision methods for analysis of plants and crops in the field (2018)
Journal Article
Smith, L., Zhang, W., Hansen, M. F., Hales, I., & Smith, M. (2018). Innovative 3D and 2D machine vision methods for analysis of plants and crops in the field. Computers in Industry, 97, 122-131. https://doi.org/10.1016/j.compind.2018.02.002

© 2018 Elsevier B.V. Machine vision systems offer great potential for automating crop control, harvesting, fruit picking, and a range of other agricultural tasks. However, most of the reported research on machine vision in agriculture involves a 2D a... Read More about Innovative 3D and 2D machine vision methods for analysis of plants and crops in the field.

Photometric stereo for three-dimensional leaf venation extraction (2018)
Journal Article
Zhang, W., Hansen, M. F., Smith, M., Smith, L., & Grieve, B. (2018). Photometric stereo for three-dimensional leaf venation extraction. Computers in Industry, 98, 56-67. https://doi.org/10.1016/j.compind.2018.02.006

© 2018 Elsevier B.V. Leaf venation extraction studies have been strongly discouraged by considerable challenges posed by venation architectures that are complex, diverse and subtle. Additionally, unpredictable local leaf curvatures, undesirable ambie... Read More about Photometric stereo for three-dimensional leaf venation extraction.