Based on KERAS’ FASHION_MNIST data set, a convolutional neural network with serial structure and parallel structure was set up for training. The serial structure can be used for deep feature mining and the parallel structure can be used to describe the first impression. The results show that the parallel structure has better effect and faster speed for simple images.

中文翻译：

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并行结构和串行结构对卷积神经网络的影响

基于KERAS的FASHION_MNIST数据集，建立了串行结构和并行结构的卷积神经网络进行训练。串行结构可用于深度特征挖掘，并行结构可用于描述第一印象。结果表明，并行结构对于简单图像具有更好的效果和更快的速度。