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Pixel normalization from numeric data as input to neural networks: For machine learning and image processing

机译:从数字数据输入到神经网络的像素归一化:用于机器学习和图像处理

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摘要

Text to image transformation for input to neural networks requires intermediate steps. This paper attempts to present a new approach to pixel normalization so as to convert textual data into image, suitable as input for neural networks. This method can be further improved by its Graphics Processing Unit (GPU) implementation to provide significant speedup in computational time.
机译:用于输入到神经网络的文本到图像的转换需要中间步骤。本文试图提出一种新的像素归一化方法,以将文本数据转换为图像,作为神经网络的输入。可以通过其图形处理单元(GPU)实施进一步改进此方法,以显着加快计算时间。

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