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首页> 外文期刊>International Journal of Pattern Recognition and Artificial Intelligence >CONNECTIONIST TECHNIQUES FOR THE IDENTIFICATION AND SUPPRESSION OF INTERFERING UNDERLYING FACTORS
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CONNECTIONIST TECHNIQUES FOR THE IDENTIFICATION AND SUPPRESSION OF INTERFERING UNDERLYING FACTORS

机译:识别和抑制潜在干扰因素的连接技术

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摘要

We consider the difficult problem of identification of independent causes from a mixture of them when these causes interfere with one another in a particular manner: those considered are visual inputs to a neural network system which are created by independent underlying causes which may occlude each other. The prototypical problem in this area is a mixture of horizontal and vertical bars in which each horizontal bar interferes with the representation of each vertical bar and vice versa. Previous researchers have developed artificial neural networks which can identify the individual causes; we seek to go further in that we create artificial neural networks which identify all the horizontal bars from only such a mixture. This task is a necessary precursor to the development of the concept of "horizontal" or "vertical".
机译:当这些原因以一种特定的方式相互干扰时,我们考虑了从这些原因的混合中识别独立原因的难题:所考虑的是神经网络系统的视觉输入,这些输入是由相互潜在的相互独立的潜在原因所产生的。这个区域的原型问题是水平条和垂直条的混合,其中每个水平条干扰每个垂直条的表示,反之亦然。以前的研究人员已经开发出了可以识别各个原因的人工神经网络。我们试图走得更远,因为我们创建了人工神经网络,可以仅从这种混合物中识别出所有的水平线。这项任务是“水平”或“垂直”概念发展的必要前提。

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