Mick Turner

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We introduce a theoretical framework for estimating the matching performance of binary correlation matrices acting as hetero-associative memories. The framework is applicable to non-recursive, fully-connected systems with binary (0,1) Hebbian weights and hard-limited threshold. It can handle both full and partial matching of single or multiple data items in(More)
A system for automatically specifying a distribution of mesh sizing throughout three dimensional complex domains is presented, which aims to reduce the level of user input required to generate a mesh. The primary motivation for the creation of this system is for the production of suitable linear meshes that are sufficiently coarse for high-order mesh(More)
We describe a technique for matching a single, learned elastic model of the shape of normal chromosomes to chromosomal images. Our model has a hierarchical organisation , with increasingly coarse shape descriptions at higher levels. A problem of finding the model description most likely to have generated an image is reduced to one of matching the locations(More)
Neural networks are applied to the problem of detecting structural aberrations in chromosomes from shape. We present a simple technique for initial location of scattered chromosomal objects within multi-resolution images of human blood cells. A system for classifying located objects is also described. It is proposed that the system be applied to(More)
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