Abstract
In contrast to all previous chapters, this final discussion is more focused on mechanisms for image interpretation which are biologically-based. It naturally follows then that the processes of interest involve investigations into just how arrays of neurons, and their hierarchical and recurrent interactions in general, can be adapted to produce temporal structures which encode spatial information. Of specific interest is the Adaptive Behavioural Cognition (ABC) model. The model comprises a series of recurrent self-organising topological maps, which form a general proposal for the understanding of cognition, and the visual component of this model is the subject of this chapter.
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© 1997 Springer Science+Business Media New York
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Briscoe, G., Caelli, T. (1997). ABC: Biologically Motivated Image Understanding. In: Machine Learning and Image Interpretation. Advances in Computer Vision and Machine Intelligence. Springer, Boston, MA. https://doi.org/10.1007/978-1-4899-1816-1_8
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DOI: https://doi.org/10.1007/978-1-4899-1816-1_8
Publisher Name: Springer, Boston, MA
Print ISBN: 978-1-4899-1818-5
Online ISBN: 978-1-4899-1816-1
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