All Outputs (91)

3D Machine vision and deep learning for enabling automated and sustainable assistive physiotherapy (2024)
Conference Proceeding
Smith, L., Boyd, S., Bhatta, D., & Smith, M. (2024). 3D Machine vision and deep learning for enabling automated and sustainable assistive physiotherapy. In 2023 Congress in Computer Science, Computer Engineering, & Applied Computing (CSCE). https://doi.org/10.1109/CSCE60160.2023.00209

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.

Towards machine vision for insect welfare monitoring and behavioural insights (2022)
Journal Article
Hansen, M. F., Oparaeke, A., Gallagher, R., Karimi, A., Tariq, F., & Smith, M. L. (2022). Towards machine vision for insect welfare monitoring and behavioural insights. Frontiers in Veterinary Science, 9, Article 835529. https://doi.org/10.3389/fvets.2022.835529

Machine vision has demonstrated its usefulness in the livestock industry in terms of improving welfare in such areas as lameness detection and body condition scoring in dairy cattle. In this article, we present some promising results of applying stat... Read More about Towards machine vision for insect welfare monitoring and behavioural insights.

Eye centre localisation with convolutional neural networks in high- and low-resolution images (2022)
Journal Article
Zhang, W., & Smith, M. L. (2022). Eye centre localisation with convolutional neural networks in high- and low-resolution images. Lecture Notes in Artificial Intelligence, 13375 LNCS, 373-384. https://doi.org/10.1007/978-3-031-10522-7_26

Eye centre localisation is critical to eye tracking systems of various forms and with applications in variety of disciplines. An active eye tracking approach can achieve a high accuracy by leveraging active illumination to gain an enhanced contrast o... Read More about Eye centre localisation with convolutional neural networks in high- and low-resolution images.

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.

Quantitative potato tuber phenotyping by 3D imaging (2021)
Journal Article
Liu, J., Xu, X., Liu, Y., Rao, Z., Smith, M., Jin, L., & Li, B. (2021). Quantitative potato tuber phenotyping by 3D imaging. Biosystems Engineering, 210, 48-59. https://doi.org/10.1016/j.biosystemseng.2021.08.001

The accurate phenotyping of the external quality attributes of potato tubers is important in potato breeding. Currently, the assessment of potato tuber shape, together with eye density and depth, are based on subjective naked eye visual evaluation. H... Read More about Quantitative potato tuber phenotyping by 3D imaging.

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.

Deep 3D face recognition using 3D data augmentation and transfer learning (2020)
Conference Proceeding
Smith, M., Smith, L., Huang, N., Hansen, M., & Smith, M. (2020). Deep 3D face recognition using 3D data augmentation and transfer learning

Abstract. Deep convolutional neural networks (DCNNs) have achieved humancomparable performance on challenging 2D face databases, outperforming all previous shallow methods. However, current 3D face recognition research still focuses on non-deep-learn... Read More about Deep 3D face recognition using 3D data augmentation and transfer learning.

Optical Imaging Technology In Colonoscopy - Is There A Role For Photometric Stereo (2020)
Journal Article
Smith, M., Shandro, B. M., Emrith, K., Slabaugh, G., & Poullis, A. (in press). Optical Imaging Technology In Colonoscopy - Is There A Role For Photometric Stereo. World Journal of Gastrointestinal Endoscopy, 12(5), 138-148. https://doi.org/10.4253/wjge.v12.i5.138

Abstract Colonoscopy screening for the detection and removal of colonic adenomas is central to efforts to reduce the morbidity and mortality of colorectal cancer. However, up to a third of adenomas may be missed at colonoscopy, and the majority of p... Read More about Optical Imaging Technology In Colonoscopy - Is There A Role For Photometric Stereo.

Eye centre localisation with convolutional neural network based regression (2020)
Conference Proceeding
Zhang, W., & Smith, M. (2020). Eye centre localisation with convolutional neural network based regression. https://doi.org/10.1109/ICIVC47709.2019.8980972

This paper introduces convolutional neural network regression models based on the Inception-v3 and the DenseNet architectures for accurate and real-time eye centre localisation. At a normalised error of e < 0.05, the proposed method yields an accurac... Read More about Eye centre localisation with convolutional neural network based regression.

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.

Multispectral imaging for presymptomatic analysis of light leaf spot in oilseed rape (2019)
Journal Article
Veys, C., Chatziavgerinos, F., AlSuwaidi, A., Hibbert, J., Hansen, M., Bernotas, G., …Grieve, B. (2019). Multispectral imaging for presymptomatic analysis of light leaf spot in oilseed rape. Plant Methods, 15, Article 4. https://doi.org/10.1186/s13007-019-0389-9

Background: The use of spectral imaging within the plant phenotyping and breeding community has been increasing due its utility as a non-invasive diagnostic tool. However, there is a lack of imaging systems targeted specifically at plant science duti... Read More about Multispectral imaging for presymptomatic analysis of light leaf spot in oilseed rape.

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.

Home activity monitoring using low resolution infrared sensor array (2018)
Conference Proceeding
Tao, L., Smith, M., Volonakis, T., Tan, B., Jing, Y., Chetty, K., & Smith, M. (2018). Home activity monitoring using low resolution infrared sensor array

Abstract. Action monitoring in a home environment provides important information for health monitoring and may serve as input into a smart home environment. Visual analysis using cameras can recognise actions in a complex scene, such as someones livi... Read More about Home activity monitoring using low resolution infrared sensor array.

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.

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.