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Neural models for part-whole hierarchies

Riesenhuber, M; Dayan, P; (1997) Neural models for part-whole hierarchies. In: Mozer, MC and Jordan, MI and Petsche, T, (eds.) ADVANCES IN NEURAL INFORMATION PROCESSING SYSTEMS 9. (pp. 17 - 23). M I T PRESS

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Abstract

We present a connectionist method for representing images that explicitly addresses their hierarchical nature. It blends data from neuroscience about whole-object viewpoint sensitive cells in inferotemporal cortex(8) and attentional basis-field modulation in V4(3) with ideas about hierarchical descriptions based on microfeatures.(5,11) The resulting model makes critical use of bottom-up and top-down pathways for analysis and synthesis.(6) We illustrate the model with a simple example of representing information about faces.

Type: Proceedings paper
Title: Neural models for part-whole hierarchies
Event: 10th Annual Conference on Neural Information Processing Systems (NIPS)
Location: DENVER, CO
Dates: 1996-12-02 - 1996-12-05
ISBN: 0-262-10065-7
UCL classification: UCL > School of Life and Medical Sciences > Faculty of Life Sciences > Gatsby Computational Neuroscience Unit
URI: http://discovery.ucl.ac.uk/id/eprint/85066
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