Abstract:
:In this article, a biologically plausible and efficient object recognition system (called ORASSYLL) is introduced, based on a set of a priori constraints motivated by findings of developmental psychology and neurophysiology. These constraints are concerned with the organization of the input in local and corresponding entities, the interpretation of the input by its transformation in a highly structured feature space, and the evaluation of features extracted from an image sequence by statistical evaluation criteria. In the context of the bias-variance dilemma, the functional role of a priori knowledge within ORASSYLL is discussed. In contrast to systems in which object representations are defined manually,the introduced constraints allow an autonomous learning from complex scenes.
journal_name
Neural Computjournal_title
Neural computationauthors
Krüger Ndoi
10.1162/089976601300014583subject
Has Abstractpub_date
2001-02-01 00:00:00pages
389-410issue
2eissn
0899-7667issn
1530-888Xjournal_volume
13pub_type
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journal_title:Neural computation
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journal_title:Neural computation
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