An analysis of deep neural network models for image recognition applications

Abstract

The development of hardware technology and information technology has promoted the development of image recognition technology. Today, image recognition technology has been applied to many national defense technologies; especially target image recognition technology is widely used in the field of air threat prevention. However, nowadays, the air target recognition technology has the disadvantage of high misjudgment rate. The main reason is that the sky is too large and the distance gap makes it difficult to distinguish the target image from other noise images. This paper takes the neural network as the classification tool, through image preprocessing and contour extraction, establishes the recognition model of the target image. The simulation results of 10 data sets show that the method used in this paper is more than 85% accurate, but the error rate is only 0.7%. The simulation results show that the model designed in this paper can achieve air target recognition very well.