Michael Cree

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Range imaging is emerging as a promising alternative technology for applications that require non-contact visual inspection of object deformation and shape. Previously, we presented a solid-state full-field heterodyne range imaging device capable of capturing three-dimensional images with sub-millimetre range resolution. Using a heterodyne indirect(More)
Distance metric learning is a well studied problem in the field of machine learning, where it is typically used to improve the accuracy of instance based learning techniques. In this paper we propose a distance metric learning algorithm that is specialised for multi-label classification tasks, rather than the multiclass setting considered by most work in(More)
Similarity metrics are a core component of many information retrieval and machine learning systems. In this work we propose a method capable of learning a similarity metric from data equipped with a binary relation. By factorising the ad-jacency matrix of the relation we are able to learn target vectors for each instance. A regression model can then be(More)
Similarity metrics are a core component of many information retrieval and machine learning systems. In this work we propose a method capable of learning a similarity metric from data equipped with a binary relation. By modelling the ad-jacency matrix of the relation we are able to learn target vectors for each instance. A regression model can then be(More)
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