Lime石灰
发表于 2025-3-23 12:29:06
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抗原
发表于 2025-3-23 15:44:36
Springer Texts in Business and Economicsummarize how existing works apply differential privacy to deep learning, we divide perturbations into four categories based on different perturbation stages of deep learning with differential privacy: input perturbation, parameter perturbation, objective function perturbation, and output perturbatio
红润
发表于 2025-3-23 20:05:07
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Indelible
发表于 2025-3-23 23:24:00
https://doi.org/10.1007/978-3-031-27196-0h 26.1793 dB and 0.8517, which has better robustness than the 8 existing watermarking algorithms. The comprehensive results indicate that the proposed algorithm can commendably balance the relationship among robustness, visual transparency and watermark embedding amount in the process of watermark e
minaret
发表于 2025-3-24 04:57:26
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评论者
发表于 2025-3-24 06:59:31
From Congruent Numbers to Elliptic Curves,ning based on crowd search algorithm, and understands financial risk analysis and early warning and related theories of crowd search algorithm on the basis of literature data, and then analyzes the financial risk analysis and early warning system of memory crowd search algorithm is designed and test
捕鲸鱼叉
发表于 2025-3-24 11:36:05
https://doi.org/10.1007/978-1-4684-0255-1ss. For the network structure, the width and depth of the network are adjusted, the amount of parameters of the model is compressed. The training process is divided into the first, middle and last three stages to improve the detection performance of the model without adding extra computation. Taking
灌输
发表于 2025-3-24 15:39:00
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南极
发表于 2025-3-24 19:46:59
Marketing and Advertising in E-Commercewarning system based on the improved K-means clustering algorithm solves the problems existing in the traditional security system, which can largely avoid the problem of system omission and false alarm, and the overall performance of the power security early warning system has been greatly improved.
infringe
发表于 2025-3-25 00:50:31
https://doi.org/10.1007/978-3-031-27196-0protecting techniques in the process of delivering and end-uses of smart meter data application according to the flowing direction of smart meter data. Compared with other review papers, we analyze the merits and drawbacks in corresponding situations and provide readers a more detailed eyesight to the research status in modern smart grid.