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This paper deals with the problem of semantic transcoding of CCTV video footage. A framework is proposed that combines Computer Vision algorithms that extract visual semantics, together with Natural Language Processing that automatically builds the domain ontology from unstructured text annotations. The final aim is a system that will link the visual and(More)
In this paper we explore the distribution of training of self-organised maps (SOM) on grid middleware. We propose a two-level architecture and discuss an experimental methodology comprising ensembles of SOMs distributed over a grid with periodic averaging of weights. The purpose of the experiments is to begin to systematically assess the potential for(More)
A system for the visualization of large collections of images, facilitated by an automatically constructed visual thesaurus, is reported. A corpus-based method for extraction of terminology and ontology of a specialist domain, scene-of-crime, is outlined. The challenge when capturing information in a crime scene is how to later visualise the scene, when all(More)
In general terms the evaluation of a summary depends on how close it is to the chief points in the source text. This begets the question as to what are the chief points in the source text and how is this information used in itself in identifying the source text. This is crucially important when we discuss automatic evaluation of summaries. So the question(More)
'Integrated' classification refers to the conjunctive or competitive use of two or more (neural) classifiers. A cooperative neural network system comprising two independently trained Kohonen networks and cooperating with the help of a Hebbian network, is described. The effectiveness of such a network is demonstrated by using it to retrieve images and(More)
distances are computed in a multi-dimensional space. The axes of this space in principle relate to the features inherent in the input data. Usually, such features are chosen by neural network developers, thereby introducing a possible bias. A method of automatically generating feature sets is discussed, with specific reference to the categorisation of(More)
Visualisation techniques focus on reducing high dimensional data to a low dimensional surface or a cube. Similar dimensional reduction is attempted in the so-called 'self-organising maps'. A number of techniques have been developed to visualise categories learnt by these maps through and exemplified by the term sequential clustering. An evaluation of the(More)