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Outputs (17)

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.

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.

The application of eye-tracking technology in architecture engineering and construction industry: A systematic review (2021)
Conference Proceeding
Mahamadu, A., Prabhakaran, A., Clark, K., Dziekonski, K., Okeke, U., Zhang, W., …Aigbavboa, C. O. (2021). The application of eye-tracking technology in architecture engineering and construction industry: A systematic review. In N. Dawood, F. Pour Rahimian, & M. Sheikhkhoshkar (Eds.), Proceedings of the 21st International Conference on Construction Applications of Virtual Reality (56-64)

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)
Conference Proceeding
Kneis, B., & Zhang, W. (2020). 3D face recognition using photometric stereo and deep learning. In Proceedings of the 10th International Conference on Web Intelligence, Mining and Semantics (255–261). https://doi.org/10.1145/3405962.3405995

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.

Image segmentation of underfloor scenes using a mask regions convolutional neural network with two-stage transfer learning (2020)
Journal Article
Atkinson, G. A., Zhang, W., Hansen, M. F., Holloway, M. L., & Napier, A. A. (2020). Image segmentation of underfloor scenes using a mask regions convolutional neural network with two-stage transfer learning. Automation in Construction, 113, Article 103118. https://doi.org/10.1016/j.autcon.2020.103118

© 2020 Elsevier B.V. Enclosed spaces are common in built structures but pose a challenge to many forms of manual or robotic surveying and maintenance tasks. Part of this challenge is to train robot systems to understand their environment without huma... Read More about Image segmentation of underfloor scenes using a mask regions convolutional neural network with two-stage 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.

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.

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.

Eye centre localisation: An unsupervised modular approach (2016)
Journal Article
Zhang, W., Smith, M. L., Smith, L. N., & Farooq, A. R. (2016). Eye centre localisation: An unsupervised modular approach. Sensor Review, 36(3), 277-286. https://doi.org/10.1108/SR-06-2015-0098

© Emerald Group Publishing Limited. Purpose - This paper aims to introduce an unsupervised modular approach for eye centre localisation in images and videos following a coarse-to-fine, global-to-regional scheme. The design of the algorithm aims at ex... Read More about Eye centre localisation: An unsupervised modular approach.

Gender and gaze gesture recognition for human-computer interaction (2016)
Journal Article
Zhang, W., Smith, M. L., Smith, L. N., & Farooq, A. (2016). Gender and gaze gesture recognition for human-computer interaction. Computer Vision and Image Understanding, 149, 32-50. https://doi.org/10.1016/j.cviu.2016.03.014

© 2016 Elsevier Inc. The identification of visual cues in facial images has been widely explored in the broad area of computer vision. However theoretical analyses are often not transformed into widespread assistive Human-Computer Interaction (HCI) s... Read More about Gender and gaze gesture recognition for human-computer interaction.

Eye center localization and gaze gesture recognition for human-computer interaction (2016)
Journal Article
Zhang, W., Smith, M. L., Smith, L. N., & Farooq, A. (2016). Eye center localization and gaze gesture recognition for human-computer interaction. Journal of the Optical Society of America A, 33(3), 314-325. https://doi.org/10.1364/JOSAA.33.000314

© 2016 Optical Society of America. This paper introduces an unsupervised modular approach for accurate and real-time eye center localization in images and videos, thus allowing a coarse-to-fine, global-to-regional scheme. The trajectories of eye cent... Read More about Eye center localization and gaze gesture recognition for human-computer interaction.

Gender recognition from facial images: Two or three dimensions? (2016)
Journal Article
Zhang, W., Smith, M. L., Smith, L. N., & Farooq, A. (2016). Gender recognition from facial images: Two or three dimensions?. Journal of the Optical Society of America A, 33(3), 333-344. https://doi.org/10.1364/JOSAA.33.000333

© 2016 Optical Society of America. This paper seeks to compare encoded features from both two-dimensional (2D) and three-dimensional (3D) face images in order to achieve automatic gender recognition with high accuracy and robustness. The Fisher vecto... Read More about Gender recognition from facial images: Two or three dimensions?.