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Titlebook: Business Intelligence and Information Technology; Proceedings of BIIT Aboul Ella Hassanien,Dequan Zheng,Zhipeng Fan Conference proceedings

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樓主: Remodeling
31#
發(fā)表于 2025-3-26 23:26:58 | 只看該作者
Kazuki Matsubara,Sanpei Kageyamaectrum, magnitude spectrum, correlation, and T-Distributed Stochastic Neighboring Embedding (T-SNE) analysis. This analysis yields valuable insights from EEG data, refining the input data and making it more suitable for prediction and identification. The model‘s performance is evaluated using two di
32#
發(fā)表于 2025-3-27 03:26:45 | 只看該作者
33#
發(fā)表于 2025-3-27 09:21:39 | 只看該作者
34#
發(fā)表于 2025-3-27 10:20:12 | 只看該作者
2190-3018 nd technology, information security, automatic control technique, data mining, software development, and design, blockchain technology, big data technology, and artificial intelligence technology..978-981-97-3982-0978-981-97-3980-6Series ISSN 2190-3018 Series E-ISSN 2190-3026
35#
發(fā)表于 2025-3-27 16:52:55 | 只看該作者
Extraction of Small Resonance Signals in Strong Same-Frequency Backgroundin a strong background. When the frequency of the background signal is the same as the signal to be measured, this signal extraction of the difficulty of the process will increase sharply. This paper compares the effects of short-time Fourier transform, continuous wavelet transforms, and shallow neu
36#
發(fā)表于 2025-3-27 21:41:35 | 只看該作者
37#
發(fā)表于 2025-3-28 02:01:23 | 只看該作者
Improved Algorithm of FP-Growth Based on Strong Data Correlationd on the original FP-Growth algorithm, which sorts the strongly correlated data in advance, that is, traverses the filtered data set one more time, searches for something that has relationships in the database in advance, merge collections with the sets with strong association rules to reduce the nu
38#
發(fā)表于 2025-3-28 03:43:27 | 只看該作者
39#
發(fā)表于 2025-3-28 09:18:14 | 只看該作者
40#
發(fā)表于 2025-3-28 12:34:01 | 只看該作者
Kinect-Based Dual-Stream Spatiotemporal Convolution Human Behavior Recognition Technologyed dual-stream spatiotemporal convolution method based on Kinect to recognize human actions. Under the original dual-stream spatiotemporal convolution framework, the VGG-16 model is changed to the ResNet-50 model to convolve the bone data collected by Kinect, and then, the spatial and temporal data
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