All Outputs (12)

IYOLO-FAM: Improved YOLOv8 with feature attention mechanism for cow behaviour detection (2024)
Presentation / Conference Contribution

We introduced IYOLO-FAM (Improved YOLOv8 with Feature Attention Mechanism) for detecting cow behaviours. By leveraging the robust YOLOv8 architecture improved with Feature Attention Mechanisms (FAM), Squeeze-and-Excitation (SE) blocks and data augmen... Read More about IYOLO-FAM: Improved YOLOv8 with feature attention mechanism for cow behaviour detection.

Precision single-camera eye tracking towards cognitive health assessment (2024)
Presentation / Conference Contribution

Eye tracking has been increasingly recognised as a valuable
tool for assessing cognitive health. However, many existing eye tracking systems are often expensive, imprecise, and inconvenient, which limits their accessibility and effectiveness in clin... Read More about Precision single-camera eye tracking towards cognitive health assessment.

SPGNet: A shape-prior guided network for medical image segmentation (2024)
Presentation / Conference Contribution

Given the intricacy and variability of anatomical structures in medical images, some methods employ shape priors to constrain segmentation. However, limited by the representational capability of these priors, existing approaches often struggle to cap... Read More about SPGNet: A shape-prior guided network for medical image segmentation.

Vision detection for early signs of DD lesions and lameness within dairy cattle (2023)
Presentation / Conference Contribution

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)
Presentation / Conference Contribution

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 Contribution

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.

The application of eye-tracking technology in architecture engineering and construction industry: A systematic review (2021)
Presentation / Conference Contribution

Despite the scholarly attention on eye-tracking technology in the AEC industry, no studies thus far have attempted to aggregate the findings or knowledge. To bridge this gap and to better understand the state-of-the-art of eye-tracking technology’s a... Read More about The application of eye-tracking technology in architecture engineering and construction industry: A systematic review.

3D face recognition using photometric stereo and deep learning (2020)
Presentation / Conference Contribution

Illumination variance is one of the largest real-world problems when deploying face recognition systems. Over the last few years much work has gone into the development of novel 3D face recognition methods to overcome this issue. Photometric stereo i... Read More about 3D face recognition using photometric stereo and deep learning.

Eye centre localisation with convolutional neural network based regression (2020)
Presentation / Conference Contribution

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)
Presentation / Conference Contribution

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.

Broad-leaf weed detection in pasture (2018)
Presentation / Conference Contribution

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)
Presentation / Conference Contribution

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.