The Application of Deep Learning in Image Processing is Studied Based on the Reel Neural Network Model

In recent years, with the deepening of deep learning reform and the rapid development of reeling neural network technology, the model applied by deep learning has been greatly different from the traditional, the original learning program and learning model need to be developed and changed with the progress of the times. Therefore, the purpose of this paper is to rely on the network model derived from the deep learning of reel neural networks to solve the problems in the field of image processing. Based on the technical safety code and data security protection of reticulation neural network, this paper learns in depth the computing power of reel neural network while taking into account the deep learning corresponding to the refragstortic neural network model, and then collects, organizes and analyzes the information related to image processing, uses sandbox simulation operation, modeling, and a variety of intelligent algorithms to get the final result. This paper mainly uses the target detection algorithm to experiment. The experimental results show that the application of co product neural network model deep learning in image processing can be improved more effectively by using suitable algorithms.