营养品 发表于 2025-3-21 19:18:10
书目名称New Trends in Disruptive Technologies, Tech Ethics and Artificial Intelligence影响因子(影响力)<br> http://figure.impactfactor.cn/if/?ISSN=BK0665928<br><br> <br><br>书目名称New Trends in Disruptive Technologies, Tech Ethics and Artificial Intelligence影响因子(影响力)学科排名<br> http://figure.impactfactor.cn/ifr/?ISSN=BK0665928<br><br> <br><br>书目名称New Trends in Disruptive Technologies, Tech Ethics and Artificial Intelligence网络公开度<br> http://figure.impactfactor.cn/at/?ISSN=BK0665928<br><br> <br><br>书目名称New Trends in Disruptive Technologies, Tech Ethics and Artificial Intelligence网络公开度学科排名<br> http://figure.impactfactor.cn/atr/?ISSN=BK0665928<br><br> <br><br>书目名称New Trends in Disruptive Technologies, Tech Ethics and Artificial Intelligence被引频次<br> http://figure.impactfactor.cn/tc/?ISSN=BK0665928<br><br> <br><br>书目名称New Trends in Disruptive Technologies, Tech Ethics and Artificial Intelligence被引频次学科排名<br> http://figure.impactfactor.cn/tcr/?ISSN=BK0665928<br><br> <br><br>书目名称New Trends in Disruptive Technologies, Tech Ethics and Artificial Intelligence年度引用<br> http://figure.impactfactor.cn/ii/?ISSN=BK0665928<br><br> <br><br>书目名称New Trends in Disruptive Technologies, Tech Ethics and Artificial Intelligence年度引用学科排名<br> http://figure.impactfactor.cn/iir/?ISSN=BK0665928<br><br> <br><br>书目名称New Trends in Disruptive Technologies, Tech Ethics and Artificial Intelligence读者反馈<br> http://figure.impactfactor.cn/5y/?ISSN=BK0665928<br><br> <br><br>书目名称New Trends in Disruptive Technologies, Tech Ethics and Artificial Intelligence读者反馈学科排名<br> http://figure.impactfactor.cn/5yr/?ISSN=BK0665928<br><br> <br><br>Gastric 发表于 2025-3-22 00:03:49
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Juan F. de Paz Santana,Daniel H. de la Iglesia,AlfIncludes recent research on disruptive technologies, tech ethics, and artificial intelligence.Presents the proceedings of Conference on (DiTTEt 2021) which was held in Salamanca, Spain, September 15-1思乡病 发表于 2025-3-22 15:41:01
Deep Learning Based Human to Human Interaction Detection Using Wireless Fidelitygnals when there is a human activity or human-to-human interaction. The paper uses the deep learning method which is used to classify five human-to-human interactions in three different phases. The proposed convolutional neural network can identify 5 classes (approaching, departing, high-five, hands核心 发表于 2025-3-22 17:51:05
Estimating Time Lost on Semaphores with Deep Learningian time lost in a specific intersection of the city of Salamanca (Spain). The best of our models has an average Mean Absolute Error (MAE) lower than a second using 10-fold cross-validation. Finally, we discuss mechanisms to generalize our models to other intersections using only a reduced amount of不成比例 发表于 2025-3-22 21:51:05
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Opinion Mining for Curriculum Enrichment Using Self-Organizing Maps company to find customers and employees necessities. The analysis of these results will make it possible to undertake corrective actions to improve the opinion of the user in relation to their work development. In all experiments, using SOM, we achieve a quantization error below 0.02. In addition,Organization 发表于 2025-3-23 07:03:54
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