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Titlebook: Computational Science – ICCS 2019; 19th International C Jo?o M. F. Rodrigues,Pedro J. S. Cardoso,Peter M.A Conference proceedings 2019 Spri

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樓主: onychomycosis
41#
發(fā)表于 2025-3-28 14:58:12 | 只看該作者
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Computational Science – ICCS 2019978-3-030-22741-8Series ISSN 0302-9743 Series E-ISSN 1611-3349
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發(fā)表于 2025-3-28 23:48:45 | 只看該作者
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發(fā)表于 2025-3-29 03:35:57 | 只看該作者
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Lecture Notes in Computer Sciencehttp://image.papertrans.cn/c/image/233083.jpg
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發(fā)表于 2025-3-29 12:22:07 | 只看該作者
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發(fā)表于 2025-3-29 17:28:05 | 只看該作者
Application of Continuous Time Quantum Walks to Image Segmentationrom its classical counterpart?[.], presents and compares two versions of the solution regarding calculation of pixel-segment association: the version using limiting distribution of the walk and the version using last step distribution. The obtained results vary in terms of accuracy and possibilities
48#
發(fā)表于 2025-3-29 23:14:30 | 只看該作者
Synchronized Detection and Recovery of Steganographic Messages with Adversarial Learningng to learn a good steganographic algorithm. To handle the problem of embedding secret messages into the specific medium, we design a novel adversarial module to learn the steganographic algorithm, and simultaneously train three modules called generator, discriminator and steganalyzer. Different fro
49#
發(fā)表于 2025-3-30 03:04:00 | 只看該作者
50#
發(fā)表于 2025-3-30 05:20:38 | 只看該作者
A Fast ,NN-Based Approach for Time Sensitive Anomaly Detection over Data Streamsy used criteria for determining outliers is based on the number of their neighboring elements, which are referred to as Nearest Neighbors (NN). Existing .NN-based Anomaly Detection (.NN-AD) algorithms cannot detect streaming outliers, which present time sensitive abnormal behavior characteristics in
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