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Titlebook: Human Centered Computing; 4th International Co Yong Tang,Qiaohong Zu,José G. Rodríguez García Conference proceedings 2019 Springer Nature S

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51#
發(fā)表于 2025-3-30 12:03:20 | 只看該作者
52#
發(fā)表于 2025-3-30 13:05:31 | 只看該作者
Brain Computer Interface Application for People with Movement Disabilities,phalography data extracted from a MUSE headband for manipulating real life household appliances connected to an Arduino system. Experimental results indicated that people with limited training process were capable to use the prototype with manageable level of error.
53#
發(fā)表于 2025-3-30 18:48:19 | 只看該作者
Research on Embedded and Monitoring Test Technology of C4ISR System,application flow of a C.ISR system, including embedded test process and monitoring test process. The test environment has been successfully applied in many projects, which can realize the recurrence, positioning, confirmation and verification of interface and process problems encountered in the C.ISR system maintenance guarantee process.
54#
發(fā)表于 2025-3-30 21:54:08 | 只看該作者
Reinforcement Learning Based Cooperation Transmission Policy for HetNets with CoMP Technology,stations in CoMP system. Using the method of reinforcement learning (RL), a semi-dynamic collaboration scheme that can be learned autonomously is proposed. Simulations show that this solution has a significant effect on improving system throughput and improving edge user rates.
55#
發(fā)表于 2025-3-31 02:04:45 | 只看該作者
Capacity Estimation of Time-Triggered Ethernet Network Based on Complex Network Theory,ork and the edge betweenness can be established and utilized to estimate the capacity. Then, reasonability of the capability estimation method can be verified by relative experiment. With this research, it is more efficient to design and plan TTE network flow.
56#
發(fā)表于 2025-3-31 09:00:44 | 只看該作者
Single Image Super-Resolution by Parallel CNN with Skip Connections and ResNet,e input of the next layer, which is the skip connection. We also borrowed the idea of Residual Net. The network learns the residuals between high-resolution images and low-resolution images. Therefore, the algorithm proposed in this paper not only achieves the most advanced performance, but also achieves faster calculations.
57#
發(fā)表于 2025-3-31 11:08:51 | 只看該作者
58#
發(fā)表于 2025-3-31 17:19:14 | 只看該作者
59#
發(fā)表于 2025-3-31 18:55:46 | 只看該作者
60#
發(fā)表于 2025-4-1 00:38:23 | 只看該作者
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