burgeon
发表于 2025-3-21 16:10:32
书目名称Artificial Neural Networks and Machine Learning – ICANN 2024影响因子(影响力)<br> http://impactfactor.cn/2024/if/?ISSN=BK0167619<br><br> <br><br>书目名称Artificial Neural Networks and Machine Learning – ICANN 2024影响因子(影响力)学科排名<br> http://impactfactor.cn/2024/ifr/?ISSN=BK0167619<br><br> <br><br>书目名称Artificial Neural Networks and Machine Learning – ICANN 2024网络公开度<br> http://impactfactor.cn/2024/at/?ISSN=BK0167619<br><br> <br><br>书目名称Artificial Neural Networks and Machine Learning – ICANN 2024网络公开度学科排名<br> http://impactfactor.cn/2024/atr/?ISSN=BK0167619<br><br> <br><br>书目名称Artificial Neural Networks and Machine Learning – ICANN 2024被引频次<br> http://impactfactor.cn/2024/tc/?ISSN=BK0167619<br><br> <br><br>书目名称Artificial Neural Networks and Machine Learning – ICANN 2024被引频次学科排名<br> http://impactfactor.cn/2024/tcr/?ISSN=BK0167619<br><br> <br><br>书目名称Artificial Neural Networks and Machine Learning – ICANN 2024年度引用<br> http://impactfactor.cn/2024/ii/?ISSN=BK0167619<br><br> <br><br>书目名称Artificial Neural Networks and Machine Learning – ICANN 2024年度引用学科排名<br> http://impactfactor.cn/2024/iir/?ISSN=BK0167619<br><br> <br><br>书目名称Artificial Neural Networks and Machine Learning – ICANN 2024读者反馈<br> http://impactfactor.cn/2024/5y/?ISSN=BK0167619<br><br> <br><br>书目名称Artificial Neural Networks and Machine Learning – ICANN 2024读者反馈学科排名<br> http://impactfactor.cn/2024/5yr/?ISSN=BK0167619<br><br> <br><br>
Circumscribe
发表于 2025-3-21 22:13:01
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蚊帐
发表于 2025-3-22 02:38:13
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FRET
发表于 2025-3-22 06:01:38
Addressing the Privacy and Complexity of Urban Traffic Flow Prediction with Federated Learning and Sorporate external factors into the road network, which helps the model to consider multiple factors affecting traffic flow more fully. Evaluation on the real dataset shows that our framework can achieve high accuracy while preserving privacy.
SAGE
发表于 2025-3-22 10:08:53
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财产
发表于 2025-3-22 15:12:12
Mark R. Harrigan,John P. Deveikisorporate external factors into the road network, which helps the model to consider multiple factors affecting traffic flow more fully. Evaluation on the real dataset shows that our framework can achieve high accuracy while preserving privacy.
分发
发表于 2025-3-22 18:43:57
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LEVER
发表于 2025-3-23 00:08:27
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Hemiplegia
发表于 2025-3-23 03:23:56
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弄脏
发表于 2025-3-23 09:35:44
Cross-Modal Attention Alignment Network with Auxiliary Text Description for Zero-Shot Sketch-Based Io textual information involved. However, the growing prevalence of Large-scale pre-trained Language Models (LLMs), which have demonstrated great knowledge learned from web-scale data, can provide us with an opportunity to conclude collective textual information. Our key innovation lies in the usage