Titlebook: Intelligent Computing Theories and Application; 16th International C De-Shuang Huang,Vitoantonio Bevilacqua,Abir Hussai Conference proceedi

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Cantankerous

Time Sequence Features Extraction Algorithm of Lying Speech Based on Sparse CNN and LSTMes and time sequence features proposed in this paper had a higher detection rate and good scalability. In a word, the Sparse-CNN-LSTM feature extraction model provided a new idea for the research of lying speech detection.

Emg827

An Improved Conditional Generative Adversarial Network for Microarray Data threshold is proposed. On one hand, to improve the convergence probability of the CGAN, a feature matching penalty strategy is proposed in this study, which consists in finding a Nash equilibrium to a two-player non-cooperative game. On the other hand, to overcome the problem of the “dirty” samples

简略

Lipoprotein

Paying Deep Attention to Both Neighbors and Multiple Tasksd the weighting scores are based on the similarity between the target task and the other tasks. The outputs of the neighbor attention layer and task attention layer are concatenated as the output of one dual-attention. To train the parameters of the network, we minimize the classification losses and

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Unsupervised Multi-omic Data Fusion: The Neural Graph Learning Networkate of the art. The method has a great intrinsic flexibility as it can be customized according to the complexity of the tasks and it has a lot of room for future improvements compared to more fine-tuned methods, opening the way for future research.

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火海

Yan Xu,Jingwei Wang,Lianbo Ma,Junfeng Zhao,Xiaolong Shen

Inferior

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