Image recognition algorithms based on deep learning

Abstract

Convolutional neural network is a very important research direction in deep learning technology. According to the current development of convolutional network, in this paper, convolutional neural networks are induced. Firstly, this paper induces the development process of convolutional neural network; then it introduces the structure of convolutional neural network and some typical convolutional neural networks. Finally, several examples of the application of deep learning is introduced.

A recommendation model for college majors based on deep learning and clustering algorithms

“…By default, the training set is composed of 80% of the graduates' learning data, which is used to train the model and find a way to predict the scores of professional courses from the scores of freshmen courses; The validation set consists of 20% of the graduate's learning data for validating and correcting the parameters of the model; The test set consists of scores from freshmen and is used to predict the scores of professional courses using the trained model. The continuous iterative optimization is used to obtain the final model, so as to predict the scores of their major courses and choose the most suitable major [14,15]. Specifically, a three-layer BP neural network is used here to implement this model: input layer, hidden layer, output layer.…”