Object recognition based on combinatorial neural network

In recent years, the identification of flying objects in the air has been the focus of scholars' research, whether it is military or life, the application of UAV is more and more extensive. This paper presents a combined neural network method for classification and recognition of drones, birds and clutter. First, CNN is combined with recurrent neural network to improve network performance, and then it is combined with attention mechanism at different positions, which can play a role in regulating the features obtained by convolution and the output of recurrent network, etc. Finally, the results are input into the classifier optimized by optimization algorithm for classification. This method has better recognition effect than random forest, particle swarm BP algorithm, CNN combined with recurrent neural network algorithm, etc. The recognition rate of UAV reaches 0.99. The results of different algorithms are fused at decision level to achieve better results.