[Retracted] Design and Proofreading of the English-Chinese Computer-Aided Translation System by the Neural Network
Table 1
Common NN models.
Common NN models
Simple understanding
Applicable fields
Convolutional neural network (CNN)
Taking image processing as an example, convolution no longer processes each pixel information input of the image like a NN but processes a small pixel area on the image, which can significantly reduce the number of weights
Image field
Recurrent neural network (RNN)
RNN can learn the associations between data. For example, in language data, each word in the language has its order correlation
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Composition
Generative adversarial network (GAN)
Data can be created by GAN. The process is more like human learning and practice to continuously strengthen a certain skill, and training is the correction of errors in the process of learning. GAN will generate meaningful data based on random numbers or data closer to the actual meaning
