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TY - GEN ID - cogprints526 UR - http://cogprints.org/526/ A1 - Leow, Wee Kheng A1 - Miikkulainen, Risto Y1 - 1997/// N2 - VISOR is a large connectionist system that shows how visual schemas can be learned, represented, and used through mechanisms natural to neural networks. Processing in VISOR is based on cooperation, competition, and parallel bottom-up and top-down activation of schema representations. Simulations show that VISOR is robust against noise and variations in the inputs and parameters. It can indicate the confidence of its analysis, pay attention to important minor differences, and use context to recognize ambiguous objects. Experiments also suggest that the representation and learning are stable, and its behavior is consistent with human processes such as priming, perceptual reversal, and circular reaction in learning. The schema mechanisms of VISOR can serve as a starting point for building robust high-level vision systems, and perhaps for schema-based motor control and natural language processing systems as well. KW - visual schemas KW - schema learning KW - priming KW - perceptual reversal KW - circular reaction KW - schema hierarchy KW - hierarchical learning KW - robustness TI - Visual Schemas in Neural Networks for Object Recognition and Scene Analysis SP - 161 AV - public EP - 200 ER -