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樓主: Menthol
41#
發(fā)表于 2025-3-28 17:04:20 | 只看該作者
The Norwegian Wave Model NOWAMOhe conversation going. However, not everyone has sketch basis, the method of using sketch to facilitate the exchange requires not only the foundation of sketch, but also the ability to sketch in a short period of time. Therefore, according to design and apply a set of experiments, we focus on analyz
42#
發(fā)表于 2025-3-28 22:10:50 | 只看該作者
https://doi.org/10.1007/1-4020-4028-8blems. It has developed into one of the important tasks in knowledge graphs and has received extensive attention from scholars in recent years. Through entity alignment, data from multiple isolated knowledge graphs with different sources and modes can be summarized and classified, forming a more inf
43#
發(fā)表于 2025-3-29 00:05:32 | 只看該作者
Australian Entrepreneurial Universities,s strong volatility, therefore the short-term accurate prediction of solar irradiance is of great significance to maintain the stable operation of the power grid. This work presents a novel decomposition integrated deep learning model, VMD-AC-BiLSTM, is proposed for ultra-short-term prediction of so
44#
發(fā)表于 2025-3-29 06:58:26 | 只看該作者
45#
發(fā)表于 2025-3-29 10:19:49 | 只看該作者
46#
發(fā)表于 2025-3-29 13:24:27 | 只看該作者
Malcolm J. Bowman,Wayne E. Esaiaspment of forgery detection is urgently needed. Most of the existing forgery detection technique are based on artifacts and detail features, which are greatly affected by the resolution, and its generalization ability needs to be improved. In this paper, a multi-modal fusion forgery detection model a
47#
發(fā)表于 2025-3-29 19:25:37 | 只看該作者
https://doi.org/10.1007/978-3-642-18782-7cess such huge volume of big data in an energy efficient manner is a popular topic in both industry and academia area. In this work, we discuss how to implement a hybrid transactional and analytical processing database to provide energy efficient big data processing capability. More specifically, Po
48#
發(fā)表于 2025-3-29 20:17:14 | 只看該作者
https://doi.org/10.1007/978-3-319-73159-9 pretraining models typically utilize BERT models to learn word embeddings at the character level, disregarding the semantic relationships between phrases. They also pay less attention to long-distance dependencies within sentences. Additionally, the datasets suffer from challenges such as small sca
49#
發(fā)表于 2025-3-30 03:47:24 | 只看該作者
Charles E.M. Pearce,F.M. Pearceal innovation. For the function of fitting analysis of a given function image, there is no public software on the market that uses the idea of genetic algorithm to solve the problem of function fitting. In order to make up for the insufficiency of the existing software and seize the opportunity of f
50#
發(fā)表于 2025-3-30 07:50:15 | 只看該作者
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