Convolutional neural network in the images colorization problem

M. Bulygin, M. Gayanova, A. M. Vulfin, A. Kirillova, R. Gayanov
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引用次数: 1

Abstract

Object of the research are modern structures and architectures of neural networks for image processing. Goal of the work is improving the existing image processing algorithms based on the extraction and compression of features using neural networks using the colorization of black and white images as an example. The subject of the work is the algorithms of neural network image processing using heterogeneous convolutional networks in the colorization problem. The analysis of image processing algorithms with the help of neural networks is carried out, the structure of the neural network processing system for image colorization is developed, colorization algorithms are developed and implemented. To analyze the proposed algorithms, a computational experiment was conducted and conclusions were drawn about the advantages and disadvantages of each of the algorithms.
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卷积神经网络中的图像着色问题
研究对象是用于图像处理的神经网络的现代结构和体系结构。以黑白图像的着色为例,对现有的基于神经网络特征提取和压缩的图像处理算法进行改进。本工作的主题是神经网络图像处理的算法使用异构卷积网络在着色问题。对基于神经网络的图像处理算法进行了分析,开发了图像着色的神经网络处理系统的结构,开发并实现了着色算法。为了分析所提出的算法,进行了计算实验,得出了每种算法的优缺点。
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