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Titlebook: Cognitive Computing – ICCC 2019; Third International Ruifeng Xu,Jianzong Wang,Liang-Jie Zhang Conference proceedings 2019 Springer Nature

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發(fā)表于 2025-3-25 04:42:27 | 只看該作者
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發(fā)表于 2025-3-25 14:16:51 | 只看該作者
Imagery Signal-Based Deep Learning Method for Prescreening Major Depressive Disorder,aged using STFT transform and a spectrogram. The EEG image data was then used in a deep learning model. As a result of the performance evaluation, 75% accuracy was shown for the classification of image depression EEGs and normal image type EEGs. As a result, low channel EEG data for deep learning ca
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發(fā)表于 2025-3-25 19:31:39 | 只看該作者
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發(fā)表于 2025-3-25 21:54:54 | 只看該作者
https://doi.org/10.1007/978-3-031-15710-3ons above we execute a Mission Engineering (ME) process that analyzes the organization’s or domain’s state of readiness. The ME process is a detailed analysis that provides an assessment of how the people, systems, knowledge, data, and processes are aligned to the operational outcomes. ME adds a lay
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發(fā)表于 2025-3-26 01:30:33 | 只看該作者
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發(fā)表于 2025-3-26 06:29:26 | 只看該作者
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發(fā)表于 2025-3-26 12:19:00 | 只看該作者
Efficient Gene Assembly and Identification for Many Genome Samples, such powerful approach to study large community of microbial species. For the unknown species in the metagenomic samples, gene assembly and identification without a reference genome is a very challenging problem. To overcome this issue, distributed gene assembly software handling multiple metagenom
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發(fā)表于 2025-3-26 13:23:58 | 只看該作者
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發(fā)表于 2025-3-26 18:34:13 | 只看該作者
Conditional Joint Model for Spoken Dialogue System,d DM separately. Recently, joint learning has made much progress in dialogue system research via taking full advantage of all supervised signals. In this paper, we propose an extension of joint model to a conditional setting. Our model does not only share knowledge between intent and slot, but also
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