We propose a quantum-weighted autoencoder network for compression computer-generated holograms. And the quantum-weighted autoencoder consists of embedding, entanglement, and measurement layers. Experimental results sh...
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The rapid growth of urbanization has led to an increasing need for efficient energy management systems to optimize energy consumption and reduce environmental impacts. Wireless sensor technology emerges as a pivotal s...
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Pipeline parallelism is essential for edge computing as it effectively consolidates the limited resources of edge devices, enabling the deployment of large Deep Neural network (DNN) models and accelerating inference p...
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The purpose of face super-resolution (FSR) is to reconstruct high-resolution (HR) face images from low-resolution (LR) inputs. With the continuous advancement of deep learning technologies, contemporary prior-guided F...
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To accurately extract Brillouin frequency shift of BOTDA with large sweeping step sizes, a novel structure of GAFCNN is proposed, combining time series coding with convolutional neural networks. The experimental data ...
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The existing multi-atlas brain network analysis methods rely on some simple fusion methods (i.e., add and concatenation) and do not consider the information redundancy caused by increased brain regions. To improve upo...
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The application performance of wireless Ad-Hoc network in the unmanned ship is affected by different electromagnetic environment, different communication distance and other factors, and the same device node shows diff...
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With the development of society and the growth of population in Haikou city, the driving school market in Haikou faces a series of challenges such as unreasonable teaching methods, cumbersome registration processes, n...
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This study explores the use of machine learning (ML) to improve initial handover performance for 5G networks by analysing fading-affected scenarios. In this study, we assess the ability of ML models to predict optimal...
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Due to significant intra-class variations and subtle inter-class differences, fine-grained images often pose challenges. In this paper, we propose a multi-level attention-enhanced network framework to address this iss...
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