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Titlebook: Artificial Intelligence and Security; 7th International Co Xingming Sun,Xiaorui Zhang,Elisa Bertino Conference proceedings 2021 Springer Na

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Compositional Parameter Synthesis feature set in the feature selection phase. Then, the feature set is turned to its projected features by the subspace model for each hypothesis. Here, a Laplacian regularization is employed to enhance the relationship of intra-class subjects. By comparing the subspace energies of projection feature
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Stanislav Böhm,Ondřej Meca,Petr Jančarm synchronization and the quantum correlation. Additionally, it is shown in the article that the process of synchronization under different parameter. Meanwhile, the artificial neural networks method is used to further study the classification of the quantum synchronization at non-zero temperature a
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Yuqi Chen,Christopher M. Poskitt,Jun Sunrough the self-learning process in the Q-learning algorithm. Numerical experiment has been done and the proposed algorithm are compared with some traditional approaches. The experimental results show that the improved Gale-Shapley algorithm proposed in this paper obtains better results than other wa
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Lecture Notes in Computer Sciencee proposed Aggregated Dilation Block (ADB) is used to capture the variations in the fine-grained scales. The response of the network to small lesion features is then reinforced by the Global Attention Block (GAB). We build a Feature Pyramid Network (FPN) based on the highly responsive output of the
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Multi-penalty Functions GANs via Multi-task Learninge. In CELEBA and CIFAR10 data sets, the experimental results show that although the number of parameters is increased, the adversarial learning stability and generated images quality are significantly improved. The performance of the novel GANs is better than most GANs models, close to state-of-the-
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Community Detection Model Based on Graph Representation and Self-supervised Learninge same time, the optimization scheme and training tricks are proposed to improve its performance. The experimental results show that the DGC model can gradually improve the community detection results through self-supervised learning, and finally surpass existing models.
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Artificial Intelligence Chronic Disease Management System Based on Medical Resource Perceptiontients through cooperation with a tertiary grade A hospital in Nanjing, and the drug compliance of chronic disease patients was 94.5%. Practice results demonstrate that the system can promote the efficient and orderly operation of the chronic disease management ecology.
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