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Titlebook: Data Science and Artificial Intelligence; First International Chutiporn Anutariya,Marcello M. Bonsangue Conference proceedings 2023 The Ed

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樓主: Opulent
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發(fā)表于 2025-3-25 04:40:32 | 只看該作者
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發(fā)表于 2025-3-25 08:49:26 | 只看該作者
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發(fā)表于 2025-3-25 23:15:57 | 只看該作者
Complications of Regional Anesthesiae to limited choices of the publicly available datasets, most of the machine learning-based classifiers were trained by the earlier versions of open-source projects that no longer represent the characteristics and properties of modern programming languages. Our experiments exhibit the feasibility an
26#
發(fā)表于 2025-3-26 03:00:33 | 只看該作者
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發(fā)表于 2025-3-26 05:26:49 | 只看該作者
https://doi.org/10.1007/978-3-319-98264-9ing method to forecast the water level dynamics of the Kapuas Kecil River and determine the optimal window size for precise predictions. Our results reveal an optimal window size of 336 h (equivalent to 14?days) for water level prediction using LSTM in this coastal region. Using this optimal window
28#
發(fā)表于 2025-3-26 09:37:00 | 只看該作者
Maria Angela Cerruto,Alessandra Masin brain-computer interfaces (BCIs). However, due to the limited amount of available data, overfitting is a common problem, especially when using a deep-learning classifier. One way to address this is by performing data augmentation. In this paper, we investigate the efficacy of the diffusion model as
29#
發(fā)表于 2025-3-26 13:05:44 | 只看該作者
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發(fā)表于 2025-3-26 18:46:18 | 只看該作者
https://doi.org/10.1007/978-3-031-35575-2l network (GAN) to create and alter images that are practically impossible for humans to distinguish from authentic ones. The development of GAN technology has led to significant improvements in image generation. This progress has made it difficult for humans to differentiate between generated image
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