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Sunderland Repository records the research produced by the University of Sunderland including practice-based research and theses.

Multi-modal novelty and familiarity detection

Panchev, Christo (2013) Multi-modal novelty and familiarity detection. BMC Neuroscience.

Item Type: Article


Journal Special Issue on Computational Neuroscience Meeting CNS 2013

Presented is further development of the architecture presented in [1] where a top-down feature-based and spatial attention have been incorporated in a large scale visual module and novelty and familiarity detectors based on the model presented in [2]. These have been developed in the perceptual (visual and auditory) and motor modalities. In addition to the novelty/familiarity detection shown in [2, 3], the architecture is able to partially recognise familiar features in each perceptual modality, and furthermore in a distributed fashion activate associated familiar features from one perceptual modality to another and/or to the motor programmes and affordances. The architecture is implemented on a mobile robot operating in a dynamic environment. The proposed distributed multi-modal familiarity detection integrated in the architecture improves the recognition and action performance in a noisy environment, as well as contributing to the multi-modal association and learning of novel objects and actions.

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Depositing User: Glenda Young


Item ID: 3760
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Date Deposited: 12 Apr 2013 10:15
Last Modified: 15 Jun 2020 13:21


Author: Christo Panchev

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Faculty of Technology
Faculty of Technology > School of Computer Science


Computing > Information Systems

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