fitful 发表于 2025-3-21 17:38:19
书目名称Artificial Intelligence影响因子(影响力)<br> http://figure.impactfactor.cn/if/?ISSN=BK0162079<br><br> <br><br>书目名称Artificial Intelligence影响因子(影响力)学科排名<br> http://figure.impactfactor.cn/ifr/?ISSN=BK0162079<br><br> <br><br>书目名称Artificial Intelligence网络公开度<br> http://figure.impactfactor.cn/at/?ISSN=BK0162079<br><br> <br><br>书目名称Artificial Intelligence网络公开度学科排名<br> http://figure.impactfactor.cn/atr/?ISSN=BK0162079<br><br> <br><br>书目名称Artificial Intelligence被引频次<br> http://figure.impactfactor.cn/tc/?ISSN=BK0162079<br><br> <br><br>书目名称Artificial Intelligence被引频次学科排名<br> http://figure.impactfactor.cn/tcr/?ISSN=BK0162079<br><br> <br><br>书目名称Artificial Intelligence年度引用<br> http://figure.impactfactor.cn/ii/?ISSN=BK0162079<br><br> <br><br>书目名称Artificial Intelligence年度引用学科排名<br> http://figure.impactfactor.cn/iir/?ISSN=BK0162079<br><br> <br><br>书目名称Artificial Intelligence读者反馈<br> http://figure.impactfactor.cn/5y/?ISSN=BK0162079<br><br> <br><br>书目名称Artificial Intelligence读者反馈学科排名<br> http://figure.impactfactor.cn/5yr/?ISSN=BK0162079<br><br> <br><br>不要严酷 发表于 2025-3-21 21:31:36
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Stochastic and Dual Adversarial GAN-Boosted Zero-Shot Knowledge Graph, generative adversarial network (GAN) has been used in zero-shot learning for KG completion. However, existing works on GAN-based zero-shot KG completion all use traditional simple architecture without randomness in generator, which greatly limits the ability of GAN mining knowledge on complex dataOverthrow 发表于 2025-3-22 14:34:48
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Region-Based Dense Adversarial Generation for Medical Image Segmentationmples, making robustness a key factor of DNNs when applied in the field of medical research. In this paper, in order to evaluate the robustness of medical image segmentation networks, we propose a novel Region-based Dense Adversary Generation (RDAG) method to generate adversarial examples. Specifica生意行为 发表于 2025-3-23 07:28:18
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