Iodine 发表于 2025-3-21 18:36:24
书目名称Intelligent Systems Design and Applications影响因子(影响力)<br> http://figure.impactfactor.cn/if/?ISSN=BK0476203<br><br> <br><br>书目名称Intelligent Systems Design and Applications影响因子(影响力)学科排名<br> http://figure.impactfactor.cn/ifr/?ISSN=BK0476203<br><br> <br><br>书目名称Intelligent Systems Design and Applications网络公开度<br> http://figure.impactfactor.cn/at/?ISSN=BK0476203<br><br> <br><br>书目名称Intelligent Systems Design and Applications网络公开度学科排名<br> http://figure.impactfactor.cn/atr/?ISSN=BK0476203<br><br> <br><br>书目名称Intelligent Systems Design and Applications被引频次<br> http://figure.impactfactor.cn/tc/?ISSN=BK0476203<br><br> <br><br>书目名称Intelligent Systems Design and Applications被引频次学科排名<br> http://figure.impactfactor.cn/tcr/?ISSN=BK0476203<br><br> <br><br>书目名称Intelligent Systems Design and Applications年度引用<br> http://figure.impactfactor.cn/ii/?ISSN=BK0476203<br><br> <br><br>书目名称Intelligent Systems Design and Applications年度引用学科排名<br> http://figure.impactfactor.cn/iir/?ISSN=BK0476203<br><br> <br><br>书目名称Intelligent Systems Design and Applications读者反馈<br> http://figure.impactfactor.cn/5y/?ISSN=BK0476203<br><br> <br><br>书目名称Intelligent Systems Design and Applications读者反馈学科排名<br> http://figure.impactfactor.cn/5yr/?ISSN=BK0476203<br><br> <br><br>Obedient 发表于 2025-3-22 00:16:48
Deep Learning Approach for Autonomous Spacecraft Landing,Therefore in this research a simulation is created as realistic as possible considering required physics parameters. Data has been collected while landing a spacecraft, trained deep neural network, and deployed those DNN into simulator.雇佣兵 发表于 2025-3-22 01:34:54
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OP-FedELM: One-Pass Privacy-Preserving Federated Classification via Evolving Clustering Method and cluster training datasets at the clients. Further, it will reduce the computational training time of ELM and communication overhead. At the server, we employed a meta-clustering algorithm to cluster the updates from the clients. We also proposed another one-shot FL algorithm called privacy-preservinevasive 发表于 2025-3-22 11:44:07
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Unveiling Deepfakes: Convolutional Neural Networks for Detection,visualize the training progress. This method contributes to the growing field of deepfake detection and offers a potential solution to combat the spread of manipulated media. The model obtains a validation accuracy of around 53.7% and a training accuracy of about 92%.arrogant 发表于 2025-3-22 18:25:19
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