Aiming at the practical application requirements of small dark target recognition for underwater unmanned aerial vehicles,a underwater laser gating imaging target recognition network based on convolutional neural network is designed to classifyand identify underwater multiple targets. The integrated tool HLS transplants the network into the FPGA for circuitimplementation. Firstly, the algorithm is designed to verify the realization of the convolutional neural network. Then theunderwater target recognition experiment is carried out on the implemented convolutional neural network circuit. Thenetwork identification accuracy rate is 94% for the three types of underwater target used in the experiment, which verifiesthe feasibility of convolutional neural network implementation in FPGA.
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