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Titlebook: Digital Multimedia Communications; 20th International F Guangtao Zhai,Jun Zhou,Xiaokang Yang Conference proceedings 2024 The Editor(s) (if

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21#
發(fā)表于 2025-3-25 07:12:19 | 只看該作者
Digital Multimedia Communications978-981-97-3623-2Series ISSN 1865-0929 Series E-ISSN 1865-0937
22#
發(fā)表于 2025-3-25 08:45:56 | 只看該作者
Contemporary Statistical Methods,ns. The experimental validation demonstrates that our method obtains promising objective performance and consistent visual results across various real-world underwater images compared to other eight UIE methods. Our example code and datasets are publicly available at ..
23#
發(fā)表于 2025-3-25 13:41:16 | 只看該作者
Daten importieren und exportieren,hensively integrate the information from RGB modal, are then employed to reconstruct high-resolution depth maps. In other words, The asymmetry is reflected in the fact that we only explicitly update the depth features. The effectiveness of our approach is demonstrated through quantitative and qualit
24#
發(fā)表于 2025-3-25 16:17:34 | 只看該作者
,Hilfsmittel für die Inferenzstatistik,ourier channel attention super-resolution network (WFCASR) to enhance the residual block by incorporating the wide activation mechanism and FCA. Results in the development of. By integrating the FCA block and the wide activation mechanism into our network, the high-frequency information can be effec
25#
發(fā)表于 2025-3-25 22:56:48 | 只看該作者
R-Loops and Mitochondrial DNA Metabolism, a novel Attention-guided Coupled Feature Fusion Module (ACFFM) that introduces Self-Refinement Coefficients (SRCs) generated from cross-layer fusion to weight the original layer images. This two-stage fusion approach effectively utilizes information from different scales to alleviate the impact of
26#
發(fā)表于 2025-3-26 03:55:44 | 只看該作者
27#
發(fā)表于 2025-3-26 04:32:15 | 只看該作者
28#
發(fā)表于 2025-3-26 11:19:29 | 只看該作者
29#
發(fā)表于 2025-3-26 12:56:06 | 只看該作者
30#
發(fā)表于 2025-3-26 17:42:12 | 只看該作者
Introduction: The Sage of Love,echanism, to capture the individual behaviors. The empirical analysis reveals the dynamic behavior and complexity of rumor propagation. The V-SEIR model is evaluated in different network topologies and the impact of each metric parameter is verified. By comparing the V-SEIR model with the classic pr
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