マスク方式によるニューロ紙幣識別機の開発

抄録

Recently, many applications of neural networks (NN) to commercial products have been reported. We have already considered an application of NN to bill money recognition machines. We have also confirmed that the recognition ability using NN is better than the conventional method based on trial and error. However, the size of the NN may become an obstacle to produce commercial recognition machines. We propose a random mask method which is capable of condensing input pixels in a simple way to solve this problem. Using the proposed method, we show that various kinds of bill moneys such as Japanese yens, Korean wons, and American dollars can be classified by a conventional recognition machine and 32-bit computer even if they are mixed in a random way.