关键词: 深度学习, 图像识别, 卷积神经网络, 胶囊网络, 迁移学习, 非监督学习

Abstract: As an important technical means in the field of image recognition, deep learning has broad application prospects. Carrying out image recognition technology research has important theoretical and practical significance for promoting the development of computer vision and artificial intelligence. The application of deep learning in image recognition gives a review. The origin of deep learning is introduced. Deep learning models such as deep belief network, convolutional neural network, cyclic neural network, generated confrontation network and capsule network are analyzed. The improved models of each deep learning model are compared and analyzed one by one. In this paper, the research results of deep learning in image recognition applications such as face recognition, medical image recognition and remote sensing image classification  are summarized. The existing researches are worth discussing. The development trend of deep learning in the field of image recognition is carried out. The discussion points out that the effective use of migration learning technology to identify small sample data, the use of unsupervised learning and semi-supervised learning to identify images, how to effectively identify video images and the theoretical significance of the model are further directions in this field.

Key words: deep learning, image recognition, convolutional neural network, capsule network , transfer learning, unsupervised learning