可乐
发表于 2025-3-21 17:04:01
书目名称Artificial Neural Networks in Pattern Recognition影响因子(影响力)<br> http://figure.impactfactor.cn/if/?ISSN=BK0162680<br><br> <br><br>书目名称Artificial Neural Networks in Pattern Recognition影响因子(影响力)学科排名<br> http://figure.impactfactor.cn/ifr/?ISSN=BK0162680<br><br> <br><br>书目名称Artificial Neural Networks in Pattern Recognition网络公开度<br> http://figure.impactfactor.cn/at/?ISSN=BK0162680<br><br> <br><br>书目名称Artificial Neural Networks in Pattern Recognition网络公开度学科排名<br> http://figure.impactfactor.cn/atr/?ISSN=BK0162680<br><br> <br><br>书目名称Artificial Neural Networks in Pattern Recognition被引频次<br> http://figure.impactfactor.cn/tc/?ISSN=BK0162680<br><br> <br><br>书目名称Artificial Neural Networks in Pattern Recognition被引频次学科排名<br> http://figure.impactfactor.cn/tcr/?ISSN=BK0162680<br><br> <br><br>书目名称Artificial Neural Networks in Pattern Recognition年度引用<br> http://figure.impactfactor.cn/ii/?ISSN=BK0162680<br><br> <br><br>书目名称Artificial Neural Networks in Pattern Recognition年度引用学科排名<br> http://figure.impactfactor.cn/iir/?ISSN=BK0162680<br><br> <br><br>书目名称Artificial Neural Networks in Pattern Recognition读者反馈<br> http://figure.impactfactor.cn/5y/?ISSN=BK0162680<br><br> <br><br>书目名称Artificial Neural Networks in Pattern Recognition读者反馈学科排名<br> http://figure.impactfactor.cn/5yr/?ISSN=BK0162680<br><br> <br><br>
sacrum
发表于 2025-3-21 22:08:58
K. Meßmer,H. Cotta,M. E. Müllers, which avoids the need for retraining the model. We perform experiments using the PASCAL-VOC2007 dataset. While the baseline SSD has 22M parameters and an mAP score of 77.20, the use of the SFCM (one of the plugins we used) increases the mAP score to 78.82 and the number of parameters to 25M.
演讲
发表于 2025-3-22 00:58:08
https://doi.org/10.1007/978-3-642-75445-6ness against noisy inputs. Our empirical results show that the new training regime improves the performance of echo state networks in an open loop setup under high noise and generally improves their performance in closed loop setups.
含铁
发表于 2025-3-22 04:56:00
Deutscher Bergbau in Geschichte und Ethos,r performance on NED and introduce a strategy to scale it to hundreds of thousands of formal names. Our experiments on several datasets for alias detection demonstrate that our system is capable of obtaining superior results with a large margin compared to other state-of-the-art systems.
高度赞扬
发表于 2025-3-22 09:44:39
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粗糙
发表于 2025-3-22 16:02:24
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毛细血管
发表于 2025-3-22 18:35:12
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hankering
发表于 2025-3-23 00:30:35
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RUPT
发表于 2025-3-23 02:22:08
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大猩猩
发表于 2025-3-23 08:14:07
über die Ursache des Geburtseintrittsmethod based on CNN and handcrafted features. Furthermore, a novel analysis technique for deep similarity networks is introduced for the purpose of finding relevant image regions. The proposed approach is evaluated qualitatively on video recordings of the German Broadcasting Archive.