宣告无效
发表于 2025-3-21 16:04:15
书目名称Collaborative Computing: Networking, Applications and Worksharing影响因子(影响力)<br> http://impactfactor.cn/if/?ISSN=BK0229419<br><br> <br><br>书目名称Collaborative Computing: Networking, Applications and Worksharing影响因子(影响力)学科排名<br> http://impactfactor.cn/ifr/?ISSN=BK0229419<br><br> <br><br>书目名称Collaborative Computing: Networking, Applications and Worksharing网络公开度<br> http://impactfactor.cn/at/?ISSN=BK0229419<br><br> <br><br>书目名称Collaborative Computing: Networking, Applications and Worksharing网络公开度学科排名<br> http://impactfactor.cn/atr/?ISSN=BK0229419<br><br> <br><br>书目名称Collaborative Computing: Networking, Applications and Worksharing被引频次<br> http://impactfactor.cn/tc/?ISSN=BK0229419<br><br> <br><br>书目名称Collaborative Computing: Networking, Applications and Worksharing被引频次学科排名<br> http://impactfactor.cn/tcr/?ISSN=BK0229419<br><br> <br><br>书目名称Collaborative Computing: Networking, Applications and Worksharing年度引用<br> http://impactfactor.cn/ii/?ISSN=BK0229419<br><br> <br><br>书目名称Collaborative Computing: Networking, Applications and Worksharing年度引用学科排名<br> http://impactfactor.cn/iir/?ISSN=BK0229419<br><br> <br><br>书目名称Collaborative Computing: Networking, Applications and Worksharing读者反馈<br> http://impactfactor.cn/5y/?ISSN=BK0229419<br><br> <br><br>书目名称Collaborative Computing: Networking, Applications and Worksharing读者反馈学科排名<br> http://impactfactor.cn/5yr/?ISSN=BK0229419<br><br> <br><br>
抱狗不敢前
发表于 2025-3-21 23:33:26
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CORE
发表于 2025-3-22 00:25:22
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armistice
发表于 2025-3-22 07:54:15
Defeating the Non-stationary Opponent Using Deep Reinforcement Learning and Opponent Modelingscenario, it is not easy to capture its behavior strategy when confronted with a long-term latent, highly dynamic and unpredictable opponent. FlipIt game can model the stealth interaction of advanced persistent threat. However, it is insufficient for traditional reinforcement learning approach to so
deviate
发表于 2025-3-22 10:37:51
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有其法作用
发表于 2025-3-22 15:44:22
D-AE: A Discriminant Encode-Decode Nets for Data Generationmain. The first is to use algorithms to learn the main features of minority class samples, and the second is to differentiate the generated data from the majority class samples. To tackle these challenges in binary classification, we propose the Discriminant-Autoencoder (D-AE) algorithm. It has two
有其法作用
发表于 2025-3-22 19:28:51
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使满足
发表于 2025-3-22 22:22:04
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留恋
发表于 2025-3-23 04:46:17
MD-TransUNet: TransUNet with Multi-attention and Dilated Convolution for Brain Stroke Lesion Segment large difference in the volume of stroke lesion areas and the great similarity between lesion areas and normal tissues, most of the existing methods for lesion segmentation cannot deal with these problems well. This paper proposes a novel network named MD-TransUNet for the segmentation of stroke le
训诫
发表于 2025-3-23 06:03:22
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