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樓主: ALOOF
21#
發(fā)表于 2025-3-25 07:25:20 | 只看該作者
22#
發(fā)表于 2025-3-25 07:39:16 | 只看該作者
,Normale und gest?rte Adaptation,ose-range gesture recognition, but fall short in range extension, ., they are unable to recognize gestures more than one meter away from considerable noise motions. In this paper, we design a long-range gesture recognition model which utilizes a novel data processing method and a customized artifici
23#
發(fā)表于 2025-3-25 14:17:00 | 只看該作者
24#
發(fā)表于 2025-3-25 18:27:05 | 只看該作者
Using All the Senses in Ecologyormation. Many people do not accept cameras deployed in their homes or workspaces. Recently, millimeter-wave (mmWave) gait recognition has been recognized as an alternative solution, which has the advantages of low power consumption and user privacy protection. However, performance analysis particul
25#
發(fā)表于 2025-3-25 22:57:12 | 只看該作者
https://doi.org/10.1007/978-3-642-97678-0often becomes the performance bottleneck. Gradient sparsification has been proposed to reduce the communication overhead. However, the sparsification only arbitrarily selects a small fraction of gradients, while the efficiency of selection dimension has been overlooked. Furthermore, gradient stalene
26#
發(fā)表于 2025-3-26 02:39:53 | 只看該作者
27#
發(fā)表于 2025-3-26 04:42:57 | 只看該作者
Observation of the Earth and its Environmentisk to DRAM is still limited by disk performance. The emerging . (NVRAM) provides a novel solution for this problem, while few existing researches have considered it. We propose a novel efficient data prefetch strategy for DL based on a heterogeneous memory system combining NVRAM with DRAM. Benefitt
28#
發(fā)表于 2025-3-26 09:10:44 | 只看該作者
29#
發(fā)表于 2025-3-26 14:35:16 | 只看該作者
G. Contopoulos,N. Voglis,C. Efthymiopouloscessfully extended to time series classification in recent years. As a generalization of the nearest subspace classifier, the performance of SRC depends on a rich set of training samples for each class, which can span as many variations of each class as possible under testing conditions. However, du
30#
發(fā)表于 2025-3-26 19:48:06 | 只看該作者
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