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Titlebook: Artificial Intelligence in China; Proceedings of the I Qilian Liang,Wei Wang,Bingcai Chen Conference proceedings 2020 Springer Nature Singa

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發(fā)表于 2025-3-23 13:24:23 | 只看該作者
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發(fā)表于 2025-3-23 16:13:14 | 只看該作者
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發(fā)表于 2025-3-23 19:31:52 | 只看該作者
Reorganisation Reader’s Digest Switzerland been examined. The imbalanced data is a special problem in target detection and classification task, where the number of one class is less than the other classes. This paper focuses on evaluating the performance of the deep support vector machine (DSVM) algorithm in dealing with imbalanced human ta
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發(fā)表于 2025-3-23 23:52:54 | 只看該作者
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發(fā)表于 2025-3-24 03:22:47 | 只看該作者
Einführung zum Prozessmanagementage for filtering and sorting data and a reduce stage for the operation of summary. We develop a model with two connected queues: one upstream queue for the data flow to access the mappers and one downstream queue for the data flow to access the reducers. Also, we analyze the latency of processing a
16#
發(fā)表于 2025-3-24 08:13:03 | 只看該作者
Einführung zum Programmmanagement situation of a heterogeneous cluster, in which the nodes have different structures. Specifically, a primary problem in Spark is that the resource allocation strategy based on the number of homogeneous processor cores cannot adapt to the heterogeneous cluster environment. To solve the above-mentione
17#
發(fā)表于 2025-3-24 12:09:11 | 只看該作者
Bearbeitung einer Fallstudie - ein Beispiel two armies and considering the influence of the terrain in StarCraft on the combat effectiveness of both sides, the concept of the terrain correction factor is introduced to establish a mathematical model. Secondly, using SparCraft is to simulate battles and generate data sets. Finally, the maximum
18#
發(fā)表于 2025-3-24 15:50:51 | 只看該作者
19#
發(fā)表于 2025-3-24 20:05:46 | 只看該作者
20#
發(fā)表于 2025-3-25 02:31:46 | 只看該作者
Einführung zum Programmmanagementcludes not only the content text, but also a large amount of comment information, among which the sentimental characteristics of comment are difficult to learn by neural network. In order to solve these problems, a rumor detection method based on comment sentiment and CNN-LSTM is proposed, and long
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