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首页> 外文期刊>International Journal of Pattern Recognition and Artificial Intelligence >FACE RECOGNITION BY ARTIFICIAL VISION SYSTEMS: A COGNITIVE PERSPECTIVE
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FACE RECOGNITION BY ARTIFICIAL VISION SYSTEMS: A COGNITIVE PERSPECTIVE

机译：人工视觉系统识别人脸：认知角度

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摘要

Cognitive development refers to the ability of a system to gradually acquire knowledge through experiences during its existence. As a consequence, the learning strategy should be represented as an integrated, online process that aims to build a model of the "world" and a continuous update of this model. Considering as reference the Modal Model of Memory introduced by Atkinson and Schiffrin, we propose an online learning algorithm for cognitive systems design. The incremental part of the algorithm is responsible of updating existing information or creating new data categories and the decremental part, to efficiently evaluate the system's performance facing partial or total loss of data. The proposed algorithm has been applied to the face recognition problem. More generally, the current approach can be extended to large-scale classification problems, to limit the memory requirements for optimal data representation and storage.
机译：认知发展是指系统通过其生存过程中的经验逐渐获取知识的能力。因此，学习策略应表示为一个集成的在线过程，旨在建立“世界”模型并对该模型进行持续更新。考虑到Atkinson和Schiffrin提出的记忆模态模型作为参考，我们提出了一种用于认知系统设计的在线学习算法。该算法的增量部分负责更新现有信息或创建新的数据类别和递减部分，以有效评估面对部分或全部数据丢失的系统性能。所提出的算法已应用于人脸识别问题。更一般而言，当前方法可以扩展到大规模分类问题，以限制最佳数据表示和存储的存储要求。

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