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LED recognition method based on deep learning in UAV optical camera communication

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Abstract

Optical camera communication (OCC) is a potential technology in unmanned aerial vehicle (UAV) communication scenes, which can be used as a complementary scheme for radio frequency (RF) technology to effectively mitigate electromagnetic interference. The UAV OCC system still has the problems of low reliability, poor robustness, and long latency. In this paper, we propose the $n$-ary image that contains binary image information with different thresholds for the LED area. In addition, the multi-spectrum fast recognition (MFR) algorithm based on deep learning is designed. The MFR algorithm combines the frequency channel attention (FCA) and the involution convolution operator, which take the $n$-ary image as input to accurately identify the LED state. The experiment results show that the proposed method can reduce the bit error rate (BER) and latency of the UAV OCC system.

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Data underlying the results presented in this paper are not publicly available at this time but may be obtained from the authors upon reasonable request.

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