Development of CNN and its Application in Education and Learning
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Yiming Zhou and Yongmei Su
This paper introduces the concept, development process, realization method and educational application of neural network in detail. Under the classification of CNN, LenNet-5, AlexNet, ZFNet and VGGNet have all been introduced and summarized in terms of structure and characteristics. As for local CNN, R-CNN, Fast R-CNN, Faster R-CNN have relevant development and optimization, and this paper will discuss relevant optimized convolutional neural network. Introduced basic part of the knowledge in and after the end of the level, we will discuss that in view of the education of CNN application and research, provide help for the education after class learning, mainly in the children's autonomous learning in the computer classified according to image feature selection so as to achieve the purpose of communicating with children, and even help children to learn image through image tagging - look at the picture and speak.In addition to the education of parents and teachers, the large amount of learning data provided by computers will provide more learning materials for children and help them to learn and classify. Organizing your thinking is easier to exercise.
Convolutional neural network; Educational learning materials; Image classification