Research on System Architecture Based on Deep Learning Convolutional Neural Network

In recent years, because deep learning technology can effectively learn features from data, it has become a powerful technical means in the field of image recognition. Research on image recognition can better promote the development of artificial intelligence and computer vision. This paper has conducted research and review of this field, introduced its important development and application, and made an attempt to promote further development in this field. Firstly, this paper introduces the structure of the network, and then introduces the common structural model of deep learning with CNN. The technical methods of reducing overfitting method, neural network visualization technology, inception structure, and transforming input images are discussed. Finally, the problems that still need to be solved in this field and the future of deep learning are introduced. It is pointed out that distributed computing, bit number reduction, migration learning, image style transformation, image generation, etc., are further research directions in the field of image recognition.