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Titlebook: Knowledge Science, Engineering and Management; 15th International C Gerard Memmi,Baijian Yang,Meikang Qiu Conference proceedings 2022 The E

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發(fā)表于 2025-3-21 17:52:51 | 只看該作者 |倒序?yàn)g覽 |閱讀模式
書目名稱Knowledge Science, Engineering and Management
副標(biāo)題15th International C
編輯Gerard Memmi,Baijian Yang,Meikang Qiu
視頻videohttp://file.papertrans.cn/545/544052/544052.mp4
叢書名稱Lecture Notes in Computer Science
圖書封面Titlebook: Knowledge Science, Engineering and Management; 15th International C Gerard Memmi,Baijian Yang,Meikang Qiu Conference proceedings 2022 The E
描述The three-volume sets constitute the refereed proceedings of the 15th International Conference on Knowledge Science, Engineering and Management, KSEM 2022, held in Singapore, during August 6–8, 2022.?.The?169?full papers presented in these proceedings were carefully reviewed and selected from?498?submissions. The papers are organized in the following topical sections:.Volume I:.Knowledge Science with Learning and AI (KSLA).Volume II:.Knowledge Engineering Research and Applications (KERA).Volume III:.Knowledge Management with Optimization and Security (KMOS).
出版日期Conference proceedings 2022
關(guān)鍵詞artificial intelligence; computational linguistics; computer networks,; computer systems; computer visio
版次1
doihttps://doi.org/10.1007/978-3-031-10986-7
isbn_softcover978-3-031-10985-0
isbn_ebook978-3-031-10986-7Series ISSN 0302-9743 Series E-ISSN 1611-3349
issn_series 0302-9743
copyrightThe Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerl
The information of publication is updating

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0302-9743 ent, KSEM 2022, held in Singapore, during August 6–8, 2022.?.The?169?full papers presented in these proceedings were carefully reviewed and selected from?498?submissions. The papers are organized in the following topical sections:.Volume I:.Knowledge Science with Learning and AI (KSLA).Volume II:.Kn
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Mario Fast Learner: Fast and?Efficient Solutions for?Super Mario Brosmes called 100 recent accuracy. The article propose a solution to speed up the training procedure and improve the experimental results. According to the experimental results, the new solution has good experimental performance under the new evaluation metrics proposed in this article.
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發(fā)表于 2025-3-22 15:20:32 | 只看該作者
Few-Shot Learning with?Self-supervised Classifier for?Complex Knowledge Base Question Answeringtraining scheme featured with self-supervised mechanism for model initialization. Our method utilizes a meta-learning classifier instead of pre-labeled tags to find the optimized search space. Experiments in this paper show that our model achieves state-of-the-art performance on CQA dataset without encoding question type.
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發(fā)表于 2025-3-22 19:49:48 | 只看該作者
Data-Driven Approach for Investigation of Irradiation Hardening Behavior of RAFM Steelon condition and alloy elements on the hardening behavior of RAFM steel was explored, and some optimal alloy elements composition was also recommended. This work will give some direction for RAFM steel research.
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0302-9743 owledge Engineering Research and Applications (KERA).Volume III:.Knowledge Management with Optimization and Security (KMOS).978-3-031-10985-0978-3-031-10986-7Series ISSN 0302-9743 Series E-ISSN 1611-3349
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