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All Outputs (6)

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.

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.