
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.
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.
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.
Developing and modifying artificial intelligence (AI) tools for genetic data.
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.