公开(公告)号：US20080140594A1

公开(公告)日：2008-06-12

申请号：US12021511

申请日：2008-01-29

Applicant: Pascal TANNHOF ,  Ghislain Imbert De Tremiolles

Inventor： Pascal TANNHOF ,  Ghislain Imbert De Tremiolles

IPC: G06F15/18

CPC classification number: G06T3/4046

Abstract: An artificial neural network (ANN) based system that is adapted to process an input pattern to generate an output pattern related thereto having a different number of components than the input pattern. The system (26) is comprised of an ANN (27) and a memory (28), such as a DRAM memory, that are serially connected. The input pattern (23) is applied to a processor (22), where it can be processed or not (the most general case), before it is applied to the ANN and stored therein as a prototype (if learned). A category is associated with each stored prototype. The processor computes the coefficients that allow the determination of the estimated values of the output pattern, these coefficients are the components of a so-called intermediate pattern (24). Assuming the ANN has already learned a number of input patterns, when a new input pattern is presented to the ANN in the recognition phase, the category of the closest prototype is output therefrom and is used as a pointer to the memory. In turn, the memory outputs the corresponding intermediate pattern. The input pattern and the intermediate pattern are applied to the processor to construct the output pattern (25) using the coefficients. Typically, the input pattern is a block of pixels in the field of scaling images.

Abstract translation: 一种基于人造神经网络（ANN）的系统，其适于处理输入模式以产生与其相关的输出模式，该输出模式具有与输入模式不同数量的分量。 系统（26）由串联连接的ANN（27）和存储器（28）（诸如DRAM存储器）组成。 将输入模式（23）应用于处理器（22），在处理器（22）被应用于ANN并作为原型存储（如果被学习）之前）处理器（22），其可被处理（最常见的情况））。 类别与每个存储的原型相关联。 处理器计算允许确定输出图案的估计值的系数，这些系数是所谓的中间图案的分量（24）。 假设ANN已经学习了许多输入模式，当在识别阶段向ANN呈现新的输入模式时，最近的原型的类别从其输出并被用作指向存储器的指针。 反过来，存储器输出相应的中间模式。 将输入图案和中间图案应用于处理器，以使用系数构造输出图案（25）。 通常，输入图案是缩放图像领域的像素块。