VER
发表于 2025-3-21 19:21:48
书目名称Artificial Neural Networks and Machine Learning – ICANN 2018影响因子(影响力)<br> http://figure.impactfactor.cn/if/?ISSN=BK0162643<br><br> <br><br>书目名称Artificial Neural Networks and Machine Learning – ICANN 2018影响因子(影响力)学科排名<br> http://figure.impactfactor.cn/ifr/?ISSN=BK0162643<br><br> <br><br>书目名称Artificial Neural Networks and Machine Learning – ICANN 2018网络公开度<br> http://figure.impactfactor.cn/at/?ISSN=BK0162643<br><br> <br><br>书目名称Artificial Neural Networks and Machine Learning – ICANN 2018网络公开度学科排名<br> http://figure.impactfactor.cn/atr/?ISSN=BK0162643<br><br> <br><br>书目名称Artificial Neural Networks and Machine Learning – ICANN 2018被引频次<br> http://figure.impactfactor.cn/tc/?ISSN=BK0162643<br><br> <br><br>书目名称Artificial Neural Networks and Machine Learning – ICANN 2018被引频次学科排名<br> http://figure.impactfactor.cn/tcr/?ISSN=BK0162643<br><br> <br><br>书目名称Artificial Neural Networks and Machine Learning – ICANN 2018年度引用<br> http://figure.impactfactor.cn/ii/?ISSN=BK0162643<br><br> <br><br>书目名称Artificial Neural Networks and Machine Learning – ICANN 2018年度引用学科排名<br> http://figure.impactfactor.cn/iir/?ISSN=BK0162643<br><br> <br><br>书目名称Artificial Neural Networks and Machine Learning – ICANN 2018读者反馈<br> http://figure.impactfactor.cn/5y/?ISSN=BK0162643<br><br> <br><br>书目名称Artificial Neural Networks and Machine Learning – ICANN 2018读者反馈学科排名<br> http://figure.impactfactor.cn/5yr/?ISSN=BK0162643<br><br> <br><br>
不公开
发表于 2025-3-21 20:35:42
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monologue
发表于 2025-3-22 03:34:45
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nonplus
发表于 2025-3-22 06:18:09
0302-9743Bio Medical systems, ML and Video-Image Processing, ML and Forensics, ML and Cybersecurity, ML and Social Media, ML in Engineering, Movement and Motion Detecti978-3-030-01423-0978-3-030-01424-7Series ISSN 0302-9743 Series E-ISSN 1611-3349
松驰
发表于 2025-3-22 12:15:25
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内疚
发表于 2025-3-22 14:36:24
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换话题
发表于 2025-3-22 19:38:41
A RNN-Based Multi-factors Model for Repeat Consumption Prediction behavior, and found that the MF-RNN gets better performance than non-factor RNN. Besides, we analyzed the differences in consumption behaviors between different cities and different regions in China.
脊椎动物
发表于 2025-3-23 01:13:54
Neural Model for the Visual Recognition of Animacy and Social Interactionture. For the generation of training data we propose a novel algorithm that is derived from dynamic human navigation models, and which allows to generate arbitrary numbers of abstract social interaction stimuli by self-organization.
Mendicant
发表于 2025-3-23 01:38:33
Wolfgang Hoffmann-Riem,Stefan Engelsng problems. In particular, we consider settings of partial observability and leverage the short-term memory capabilities of echo state networks (ESNs) to learn parameterized control policies. Using SPSA, we propose three different variants to adapt the weight matrices of an ESN to the task at hand.
谎言
发表于 2025-3-23 06:02:37
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