Enhancing Educational Insights Through Convolutional Neural Networks: A Comparative Analysis on CIFAR-10 and CIFAR-100 Datasets

Based on CIFAR-10 and CIFAR-100 data, this study explores the intrinsic relationship between convolution neural network model learning and data complexity and generalization ability. By introducing different convolution networks to mine the complexity of the samples and proposed an image recognition method based on depth neural network to achieve the optimal target recognition. The research results of this project will promote the extensive application of artificial intelligence technology in the field of education and lay a theoretical foundation for the construction of CNN -based teaching mode. Through comparative study, this paper has practical significance to improve AIDS publicity strategy.