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Titlebook: Augmented Cognition: Intelligent Technologies; 12th International C Dylan D. Schmorrow,Cali M. Fidopiastis Conference proceedings 2018 Spri

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發(fā)表于 2025-3-30 10:44:24 | 只看該作者
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發(fā)表于 2025-3-30 16:15:30 | 只看該作者
Deep Convolutional Neural Networks and Power Spectral Density Features for Motor Imagery Classificat Convolutional Neural Network (.) that is able to differentiate among four different movement intentions: left-hand movement, right-hand movement, feet movement, and tongue movement. Performance evaluation results reported a mean accuracy of . for the well-known BCI Competition IV Dataset 2a, which outperform state-of-the-art approaches.
53#
發(fā)表于 2025-3-30 17:46:57 | 只看該作者
Long Term Use Effects of a P300-Based Spelling Applicationcuracy rates for each display method. The average classification accuracies improved overall by a maximum of 21.43% for monitor display and 25.72% for HMD. However, the results of the experiment demonstrated that no statistical significant interaction existed between the two display methods.
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發(fā)表于 2025-3-30 23:08:18 | 只看該作者
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發(fā)表于 2025-3-31 02:46:15 | 只看該作者
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發(fā)表于 2025-3-31 08:26:32 | 只看該作者
https://doi.org/10.1007/978-3-540-36689-8cusses how these cognitive psychology strategies can be leveraged and utilized within ITSs in order to lead to improved outcomes. Additionally, there are suggestions on how to incorporate these strategies within ITSs.
57#
發(fā)表于 2025-3-31 12:30:25 | 只看該作者
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