HEW
发表于 2025-3-25 04:44:22
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上腭
发表于 2025-3-25 11:32:30
BatMapper-Plus: Smartphone-Based Multi-level Indoor Floor Plan Construction via Acoustic Ranging andrs can scan and produce indoor maps, but the deployment remains low. Existing smartphone-based approaches usually adopt computer vision techniques to build the 3D point cloud, at the cost of extensive image collection efforts and the risk of privacy issues. In this paper, we propose BatMapper-Plus w
APRON
发表于 2025-3-25 15:11:45
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Amendment
发表于 2025-3-25 18:03:20
FedGAN: A Federated Semi-supervised Learning from Non-IID Data of limited utility in the Internet of Things (IoT) scenarios, as they either heavily depend on high-quality labeled data or only perform well under idealized distribution conditions, which typically cannot be found in practical applications. In this work, we propose FedGAN, a Generative Adversarial
污秽
发表于 2025-3-25 22:31:52
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迁移
发表于 2025-3-26 03:11:57
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撤退
发表于 2025-3-26 08:13:22
Data Collection of IoT Devices with Different Priorities Using a Fleet of UAVsisting studies ignored the different importance of data stored in IoT devices and simply minimized the longest data collection latency of IoT devices. Then, it is possible that the data collection latency of a IoT device may be long, the data collection priority of the IoT device is high and its dat
继而发生
发表于 2025-3-26 10:16:43
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桶去微染
发表于 2025-3-26 15:47:52
0302-9743 A 2022, which was held during October 28-30, 2022. The conference took place in Dalian, China.The 95 full and 62 short papers presented in these proceedings were carefully reviewed and selected from 265 submissions. The contributions in. algorithms, systems; and applications of internet of things;i
课程
发表于 2025-3-26 18:49:39
FedALP: An Adaptive Layer-Based Approach for Improved Personalized Federated Learning global model. Furthermore, our scheme is customizable for specific PFL applications; hence it may provide a flexible strategy to effectuate a balanced performance for both the global and the local models.