All Outputs (107)

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.

Convolutional neural network ensemble learning for hyperspectral imaging-based blackberry fruit ripeness detection in uncontrolled farm environment (2024)
Journal Article
Olisah, C. C., Trewhella, B., Li, B., Smith, M. L., Winstone, B., Charles Whitfield, E., …Duncalfe, H. (2024). Convolutional neural network ensemble learning for hyperspectral imaging-based blackberry fruit ripeness detection in uncontrolled farm environment. Engineering Applications of Artificial Intelligence, 132, Article 107945. https://doi.org/10.1016/j.engappai.2024.107945

Fruit ripeness estimation models have for decades depended on spectral index features or colour-based features, such as mean, standard deviation, skewness, colour moments, and/or histograms for learning traits of fruit ripeness. Recently, few studies... Read More about Convolutional neural network ensemble learning for hyperspectral imaging-based blackberry fruit ripeness detection in uncontrolled farm environment.

Vision detection for early signs of DD lesions and lameness within dairy cattle (2023)
Conference Proceeding
Shahbaz, A., Zhang, W., & Smith, M. (in press). Vision detection for early signs of DD lesions and lameness within dairy cattle.

Digital dermatitis stands as a primary cause of lameness in dairy cows, significantly impacting various facets of productivity. This paper proposes a two-stage vision system aimed at early detection of digital dermatitis (DD) lesions, ultimately prev... Read More about Vision detection for early signs of DD lesions and lameness within dairy cattle.

Real-time livestock activity monitoring via fine-tuned faster R-CNN for multiclass cattle behaviour detection (2023)
Conference Proceeding
Ahmad, M., Zhang, W., Smith, M., Brilot, B., & Bell, M. (2023). Real-time livestock activity monitoring via fine-tuned faster R-CNN for multiclass cattle behaviour detection. In 2023 IEEE 14th Annual Ubiquitous Computing, Electronics & Mobile Communication Conference (UEMCON). https://doi.org/10.1109/uemcon59035.2023.10316066

Automated cattle activity detection plays a pivotal role in modern livestock management, significantly impacting animal welfare and operational efficiency. This paper introduces an automated approach for cattle activity detection using advanced deep... Read More about Real-time livestock activity monitoring via fine-tuned faster R-CNN for multiclass cattle behaviour detection.

Predicting multiple-target search performance using eye movements and individual differences (2023)
Presentation / Conference
Birch-Hurst, K., Jones, A. M., Ong, A., Stoker, K. M., Smith, M. L., Zhang, W., & Clark, K. (2023, August). Predicting multiple-target search performance using eye movements and individual differences. Poster presented at European Conference on Visual Perception, Paphos, Cyprus

Accuracy in visual search – the process of detecting a target amongst distractors – is critical for life-saving career searches such as radiology and airport security. These searches often contain multiple targets (e.g., a tumour and a fracture) and... Read More about Predicting multiple-target search performance using eye movements and individual differences.

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.