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All Outputs (13)

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.

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.

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.

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.

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.

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.

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.

Photometric stereo technique suitability study for plant phenotyping (2017)
Conference Proceeding
Halliday, K., Smith, L., Hansen, M., Smith, M., Bernotas, G., Scorza, L., …Smith, M. (2017). Photometric stereo technique suitability study for plant phenotyping

The dynamic quantification of growth traits is critical for building accurate modelling tools to predict plant behaviour under different growth environments, and consequently in designing strategies to improve plant health and overall yields. We are... Read More about Photometric stereo technique suitability study for plant phenotyping.

High speed, multi-scale tracing of curvilinear features with automated scale selection and enhanced orientation computation (2010)
Conference Proceeding
Wedowski, R., Farooq, A., Smith, L., & Smith, M. (2010). High speed, multi-scale tracing of curvilinear features with automated scale selection and enhanced orientation computation. In W. Smari (Ed.), International Conference on High Performance Computing and Simulation (HPCS), 2010 (410-417). https://doi.org/10.1109/HPCS.2010.5547105

We propose a new high speed line tracing algorithm based on a well known differential geometric line extraction algorithm. The previously separate steps of line detection and line tracing are performed simultaneously. This allows the exclusion of non... Read More about High speed, multi-scale tracing of curvilinear features with automated scale selection and enhanced orientation computation.