Hierarchical models of object recognition in cortex
Hierarchical models of object recognition in cortex
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DOI：
10.1038/14819
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发表时间：
1999-11-01
影响因子：
25
通讯作者：
Poggio, T
中科院分区：
文献类型：
--
作者：
Riesenhuber, M;Poggio, T
皮层中的视觉处理通常被建模为日益复杂的表示的层次结构，自然地将 Hubel 和 Wiesel 的简单细胞模型扩展到复杂细胞模型。令人惊讶的是，很少有定量模型来探索此类模型的生物学可行性，以解释对象识别等高级视觉处理的各个方面。我们描述了一种与颞下皮层生理数据一致的新分层模型，该模型解释了这种复杂的视觉任务并做出可测试的预测。该模型基于类似 MAX 的运算，应用于某些皮质神经元的输入，这些神经元可能在皮质功能中发挥一般作用。
Visual processing in cortex is classically modeled as a hierarchy of increasingly sophisticated representations, naturally extending the model of simple to complex cells of Hubel and Wiesel. Surprisingly, little quantitative modeling has been done to explore the biological feasibility of this class of models to explain aspects of higher-level visual processing such as object recognition. We describe a new hierarchical model consistent with physiological data from inferotemporal cortex that accounts for this complex visual task and makes testable predictions. The model is based on a MAX-like operation applied to inputs to certain cortical neurons that may have a general role in cortical function.