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The Notation Scanner Systems Using Resilient Backpropagation Method

机译:使用弹性反向传播方法的符号扫描仪系统

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This research proposes anotation scanner system for numerical notation. This research was supported by using resilient backpropagation algorithm and uses the music application to get a melody of musical instruments. Objects used are designed to be focused on the numerical notation symbols. To be implemented, the input image from camera will be pre-processing, image segmentation, number and symbol recognition, output sound, and to read numerical notation symbols before entering resilient backpropagation algorithm resize the image will be 21x21 pixels. By using colour filtering can reduce errors in handwriting recognition. Success rate by using 15 new sample data with 100 sample data training, the test to get a successful outcome as much as 87.9% and 12.1% error while success rate by using 15 new sample data with 50 sample data training, the test to get a successful outcome as much as 74.4% and 25.6% error.
机译:这项研究提出了一种用于数字符号的注释扫描器系统。这项研究得到了使用弹性反向传播算法的支持,并使用音乐应用程序获得了乐器的旋律。设计使用的对象集中在数字符号上。要实现,来自摄像机的输入图像将进行预处理,图像分割,数字和符号识别,输出声音,并在进入弹性反向传播算法之前读取数字符号,然后将图像调整为21x21像素。通过使用颜色过滤可以减少手写识别中的错误。通过使用15个新样本数据和100个样本数据训练的成功率,该测试获得成功结果高达87.9%和12.1%的错误,而通过使用15个新样本数据和50个样本数据训练的成功率,该测试得到一个成功率成功的结果高达74.4%和25.6%的错误。

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