两边在扩散
发表于 2025-3-21 20:07:44
书目名称Knowledge Science, Engineering and Management影响因子(影响力)<br> http://figure.impactfactor.cn/if/?ISSN=BK0544041<br><br> <br><br>书目名称Knowledge Science, Engineering and Management影响因子(影响力)学科排名<br> http://figure.impactfactor.cn/ifr/?ISSN=BK0544041<br><br> <br><br>书目名称Knowledge Science, Engineering and Management网络公开度<br> http://figure.impactfactor.cn/at/?ISSN=BK0544041<br><br> <br><br>书目名称Knowledge Science, Engineering and Management网络公开度学科排名<br> http://figure.impactfactor.cn/atr/?ISSN=BK0544041<br><br> <br><br>书目名称Knowledge Science, Engineering and Management被引频次<br> http://figure.impactfactor.cn/tc/?ISSN=BK0544041<br><br> <br><br>书目名称Knowledge Science, Engineering and Management被引频次学科排名<br> http://figure.impactfactor.cn/tcr/?ISSN=BK0544041<br><br> <br><br>书目名称Knowledge Science, Engineering and Management年度引用<br> http://figure.impactfactor.cn/ii/?ISSN=BK0544041<br><br> <br><br>书目名称Knowledge Science, Engineering and Management年度引用学科排名<br> http://figure.impactfactor.cn/iir/?ISSN=BK0544041<br><br> <br><br>书目名称Knowledge Science, Engineering and Management读者反馈<br> http://figure.impactfactor.cn/5y/?ISSN=BK0544041<br><br> <br><br>书目名称Knowledge Science, Engineering and Management读者反馈学科排名<br> http://figure.impactfactor.cn/5yr/?ISSN=BK0544041<br><br> <br><br>
他去就结束
发表于 2025-3-21 20:27:59
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misanthrope
发表于 2025-3-22 00:43:20
Boosting LightWeight Depth Estimation via Knowledge Distillationlexity and inference performance. In this paper, we propose a lightweight network that can accurately estimate depth maps using minimal computing resources. We achieve this by designing a compact model that maximally reduces model complexity. To improve the performance of our lightweight network, we
公猪
发表于 2025-3-22 06:28:36
Graph Neural Network with Neighborhood Reconnectionveness of GNNs is compromised by two limitations. First, they implicitly assume that networks are homophilous, leading to decreased performance on heterophilous or random networks commonly found in the real world. Second, they tend to ignore the known node labels, inferring node labels merely from t
idiopathic
发表于 2025-3-22 11:57:56
Critical Node Privacy Protection Based on Random Pruning of Critical Treesy obvious. Especially for critical node users, if the critical node users suffer from background knowledge attacks during data publishing, it can not only lead to the privacy information leakage of the critical user but also lead to the privacy leakage of their friends. To address this issue, we pro
Cosmopolitan
发表于 2025-3-22 14:16:23
DSEAformer: Forecasting by De-stationary Autocorrelation with Edgeboundl due to the increasing data volume and dimensionality. Current MLTF methods face challenges such as over-stationarization and distribution shift, affecting prediction accuracy. This paper proposes DSEAformer, a unique MLTF method that addresses distribution shift by normalizing and de-normalizing t
前奏曲
发表于 2025-3-22 20:04:16
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铺子
发表于 2025-3-23 00:15:59
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Picks-Disease
发表于 2025-3-23 02:30:40
RTAD-TP: Real-Time Anomaly Detection Algorithm for Univariate Time Series Data Based on Two-Parameteications. However, due to the continuous influx of data streams and the dynamic changes in data patterns, real-time anomaly detection still poses challenges. Algorithms such as SPOT, DSPOT, and FluxEV are efficient unsupervised anomaly detection algorithms for data streams, but their detection perfo
chuckle
发表于 2025-3-23 08:44:58
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