Papers

Wheat physiology predictor: predicting physiological traits in wheat from hyperspectral reflectance measurements using deep learning

Physiological trait prediction of wheat samples with convolutional neural networks.

@article{Furbank2021,
	url = {https://doi.org/10.1186/s13007-021-00806-6},
	doi = {10.1186/s13007-021-00806-6},
	issn = {1746-4811},
	year = {2021},
	month = {oct},
	day = {19},
	volume = {17},
	publisher = {Springer London},
	author = {Robert T. Furbank and Viridiana Silva-Perez and John R. Evans and Anthony G Condon and Gonzalo M. Estavillo and Wennan He and Saul Newman and Richard Poir{\'e} and Ashley Hall and Zhen He},
	title = {Wheat physiology predictor: predicting physiological traits in wheat from hyperspectral reflectance measurements using deep learning},
	journal = {Plant Methods}
}

The detection, tracking, and temporal action localisation of swimmers for automated analysis

Automated swimming analysis with convolutional neural networks on video data.

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@article{Hall_2020,
	url = {https://doi.org/10.1007/s00521-020-05485-3},
	year = {2020},
	month = {nov},
	publisher = {Springer London},
	author = {Ashley Hall and Brandon Victor and Zhen He and Matthias Langer and Marc Elipot and Aiden Nibali and Stuart Morgan},
	title = {The detection, tracking, and temporal action localisation of swimmers for automated analysis},
	journal = {Neural Computing and Applications}
}

A new paradigm to do and understand the race analyses in swimming: The application of convolutional neural networks

Swimming analysis with convolutional neural networks.

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@article{Elipot_2019,
	url = {https://commons.nmu.edu/isbs/vol37/iss1/112/},
	year = {2019},
	month = {jul},
	publisher = {International Society of Biomechanics in Sports (ISBS)},
	volume = {37},
	issue = {1},
	article = {112},
	author = {Marc Elipot and Jess Corones and Ash Hall and Brandon Victor and Matthias Langer and Stuart Morgan and Zhen He and Mark Osborne},
	title = {A new paradigm to do and understand the race analyses in swimming: The application of convolutional neural networks},
	journal = {ISBS Proceedings Archive}
}

MPCA SGD—A Method for Distributed Training of Deep Learning Models on Spark

A method for distributed training of deep neural networks specifically designed to run in low-budget environments.

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@article{Langer_2018,
	doi = {10.1109/tpds.2018.2833074},
	url = {https://doi.org/10.1109%2Ftpds.2018.2833074},
	year = {2018},
	month = {nov},
	publisher = {Institute of Electrical and Electronics Engineers (IEEE)},
	volume = {29},
	number = {11},
	pages = {2540--2556},
	author = {Matthias Langer and Ashley Hall and Zhen He and Wenny Rahayu},
	title = {MPCA SGD - A Method for Distributed Training of Deep Learning Models on Spark},
	journal = {IEEE Transactions on Parallel and Distributed Systems}
}

Computer Science Honours Thesis

Few-Shot Continuous Meta-Learning with Neural Networks. Thesis submitted for the Computer Science Honours, 2018.

Thesis ・ Literature Survey ・ Directed Study

ORCID ・ Google Scholar