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. 2023 Feb 25;40(1):27–34. [Article in Chinese] doi: 10.7507/1001-5515.202204052

表 1. Average results of automatic detection of arousal events based on the convolutional self-attention model and its variants(Inline graphic).

基于卷积注意力模型及其变体的觉醒事件自动检测平均结果(Inline graphic

网络模型 准确率(%) F1分数(%) AUPRC(%) AUROC(%)
卷积注意力模型 81.9 ± 5.0 74.9 ± 12.6 68.1 ± 17.2 78.9 ± 6.5
30 s-卷积注意力模型 81.9 ± 8.0 64.3 ± 13.3 55.7 ± 17.2 75.0 ± 7.0
基线模型 74.2 ± 9.0 65.8 ± 13.9 60.7 ± 18.9 72.3 ± 7.8
单一尺度卷积注意力模型 79.2 ± 6.7 71.3 ± 12.2 65.2 ± 17.7 76.5 ± 6.4
无SA卷积注意力模型 78.3 ± 8.0 70.4 ± 14.2 63.9 ± 18.7 75.3 ± 7.3