Research And Implementation Of Aircraft Target Recognition System Based On CNN For Remote Sensing Image

In recent years,with the rapid development of remote sensing technology,various imaging methods and remote sensing platforms with different spatial resolutions have emerged continuously,resulting in a large number of remote sensing images.Aircraft is an important target in many remote sensing image targets.The identification of aircraft targets in remote sensing images has become the focus of attention in the industry.Traditional aircraft target detection algorithms mostly extract multiple feature parameters by extracting Hu moments and affine invariant moments,and use SVM classifiers to achieve aircraft target recognition.The direct combination of features has the disadvantages of poor recognition of noise immunity,weak robustness and long time consuming.Aiming at the above-mentioned shortcomings of traditional aircraft detection methods,the aircraft identification system based on convolutional neural network model is studied to provide users with more accurate and fast aircraft identification service,which has important significance and practical value for improving the recognition effect of aircraft.The main work of the thesis is as follows:(1)Aiming at problems of the system without performing multiple aircraft identification tasks at the same time that the synergy of each module can not be played,the task management method based on Golang is designed.The user identification request of the designated airport is regarded as a task dispatched to the system for execution,so that multiple identification tasks can be executed concurrently,and the efficiency of the identification system is improved,and the user can create the next task without waiting for the current task to be executed.(2)Aiming at problems of remote sensing images that the size is large and the resolution is high,The remote sensing image is input directly from the system interface by the user,which takes a long time and is easily affected by the network transmission rate,resulting in task error,the way of image acquisition based on Sikuli is designed.On the server side,Sikuli that is one of graphical programming technology is used to simulate user behavior to obtain remote sensing images from the data source of 91 Satellite Assistant.(3)For the problem of aircraft recognition of remote sensing image,an image recognition algorithm based on convolutional neural network model is proposed.The fast and accurate RetinaNet detector is selected as the recognition model with focal loss function,and the data enhancement technology is used to expand the sample,in order to enhance the recognition efficiency of the detector.The experimental results show that the designed CNN-based remote sensing image aircraft target recognition system has better performance.