KEYWORDS: Unmanned aerial vehicles, Video, Information and communication technologies, Inspection, Networks, Antennas, Telecommunications, Solar energy, Network architectures, Internet
With the development of UAV technology, because of its advantages of low cost, easy operation and high flexibility, UAV has been applied to many fields such as transportation, patrol inspection, live broadcasting and so on. However, due to the problems of low rate, high delay and poor interaction, the task execution efficiency of UAV is not very satisfactory. In recent years, the rapid rise of 5g technology has brought another opportunity to the field of UAV. This paper proposes the application of UAV Based on 5g communication technology, which overcomes the current bottleneck of UAV. It provides a solution for the field application of UAV, and promotes the development of UAV.
In recent years, Generative Adversarial Network (GAN) has received much attention in the field of machine learning. It is an unsupervised learning model which is widely used in image, video, voice, etc. Based on GAN's two-man zero-sum game theory, the researchers proposed excellent variant algorithms such as deep convolutional GAN(DCGAN), Conditional GAN(CGAN), Least Squares GAN(LSGAN), and Boundary Equilibrium GAN (BEGAN), which has gradually overcome the problem of training imbalance and model collapse. However, the time efficiency of model training has always been a challenging problem. This paper proposes a GAN algorithm based on GPU parallel acceleration, which utilizes the powerful computing power of GPU and the advantages of multi-parallel computing, greatly reduces the time of model training, improves the training efficiency of GAN model, and achieves better modeling performance. Finally, we used the LSUN public scene dataset and the TIMIT public voice dataset to evaluate the proposed algorithm and compare it with the traditional GAN, DCGAN, LSGAN, and BEGAN algorithms. The experiment has fully proved the time advantage of the model training of the algorithm introduced in this paper.
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