Automated stone artefacts classification using machine learning
Stone artifacts are often the most abundant class of artifacts but their consistent identification is limited by the number of archaeologists with experience in their identification.
Enhancing Spontaneous Recovery after Stroke Study (ESPRESSo)
Research digital skills training 2021 Enhancing Spontaneous Recovery after Stroke Study (ESPRESSo) Prof Winston Byblow, Principal Investigator, Exercise Sciences, Prof Cathy Stinear & Prof Alan Barber, Medicine; A/Prof Arier Lee, Biostatistician, University of...
Data analytics and visualisation for improving public health and transport planning
Research digital skills training 2021 Data analytics and visualisation for improving public health and transport planning Professor Mark Gahegan, Computer Science; Assoc Professor Daniel Exeter, Epidemiology and Biostatistics; Professor David O’Sullivan, Victoria...
Coastal image classification and nalysis based on convolutional neural betworks and pattern recognition
Develop short-term eruption warning systems for Whakaari and other volcanoes Coastal image classification and analysis based on convolutional neural betworks and pattern recognition Assoc Professor Bo Liu1,2, Bin Yang1, Assoc Professor Giovanni Coco2*, Huina Wang1,...
An investigation into Leap Motion device for “gesture-as-sign”
Develop short-term eruption warning systems for Whakaari and other volcanoes An investigation into Leap Motion device for “gesture-as-sign” Lucy Boermans, Elam School of Fine Arts ; Andrew Leathwick, Centre for eResearch Home • Archive for "University...
Using Zebra Finch data and deep learning classification to identify individual bird calls from audio recordings
Using Zebra Finch data and deep learning classification to identify individual bird calls from audio recordings Ines Moran, PhD Candidate, Yen Yi Loo, PhD Candidate, Dr Kristal Cain, Senior Lecturer, Biological Sciences; Nick Young, Senior Solutions Specialist, Centre...
Towards the use of deep learning techniques for storm surge prediction
Developing a neural network to model the relationship between sea level pressure (SPL) fields and storm surge (SS) levels from a number of New Zealand tidal gauge.
Development of Machine Learning methodology for genomic research
Developing and modifying artificial intelligence (AI) tools for genetic data.
Virtual childhood obesity prevention laboratory
Virtual childhood obesity prevention laboratory Professor Ni Mhurchu, Programme Leader, Population Health. University of Auckland. Deep learning & analytics provided by Sina Masoud-Ansari, Research IT Specialist, Centre for eResearch, University of Auckland...
Centre for eResearch machine learning service
There has been significant growth in interest around machine learning and its applications to research. This has largely been driven by advances in algorithms, particularly in neural networks where the use of Graphics Processing Units (GPUs) has reduced the time to train complex or ‘deep’ neural networks by orders of magnitude. With the rise of ‘big data’, researchers are increasingly finding opportunities to apply these methods to deliver new insights.