首页>
外国专利>
Evidential confidence measure and rejection technique for use in a neural network based optical character recognition system
Evidential confidence measure and rejection technique for use in a neural network based optical character recognition system
展开▼
机译:用于基于神经网络的光学字符识别系统的证据置信度测量和剔除技术
展开▼
页面导航
摘要
著录项
相似文献
摘要
Apparatus, and an accompanying method, for use in, e.g., a neural network-based optical character recognition (OCR) system (5) for accurately classifying each individual character extracted from a string of characters, and specifically for generating a highly reliable confidence measure that would be used in deciding whether to accept or reject each classified character. Specifically, a confidence measure, associated with each output of, e.g., a neural classifier (165), is generated through use of all the neural activation output values. Each individual neural activation output provides information for a corresponding atomic hypothesis of an evidence function. This hypothesis is that a pattern belongs to a particular class. Each neural output is transformed (1650) through a pre-defined monotonic function into a degree of support in its associated evidence function. These degrees of support are then combined (1680, 1690) through an orthogonal sum to yield a single confidence measure associated with the specific classification then being produced by the neural classifier.
展开▼