2021
DOI: 10.1016/j.neucom.2020.10.104
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A few filters are enough: Convolutional neural network for P300 detection

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Cited by 19 publications
(12 citation statements)
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“…To show the technical choice of the MLP network, we also replace our MLP structure with the other deep networks, including 1D convolutional neural network (1D-CNN) [68] and transformer [69]. Existing credit scoring methods usually treat the credit scoring method as a classification method.…”
Section: The Comparison With Alternative Methodsmentioning
confidence: 99%
“…To show the technical choice of the MLP network, we also replace our MLP structure with the other deep networks, including 1D convolutional neural network (1D-CNN) [68] and transformer [69]. Existing credit scoring methods usually treat the credit scoring method as a classification method.…”
Section: The Comparison With Alternative Methodsmentioning
confidence: 99%
“…In addition, SepCNN used a single-layer separable convolutional, which theoretically required less computation than the single-layer standard CNN of Shan et al (2018) . Compared with the CNN proposed by Alvarado-González et al (2021) , SepCNN added more normalization layers for better AR-P300 classification performance.…”
Section: Methodsmentioning
confidence: 99%
“…Inspired by separable convolution ( Chollet, 2017 ), Lawhern et al proposed a compact CNN architecture consisting of a standard convolution layer, a separable convolution layer, and a fully connected layer, achieving an AUC of 0.92 in single extraction in the P300 oddball paradigm ( Lawhern et al, 2018 ). Subsequent studies gradually reduced the model complexity and proposed a simpler single-layer CNN structure ( Shan et al, 2018 ; Alvarado-González et al, 2021 ). The deep learning algorithm has achieved good performance in the classification of CS–P300.…”
Section: Introductionmentioning
confidence: 99%
“…Count References BCI2000 41 [1], [2], [3], [4], [5], [6], [7], [8], [9], [10], [11], [12], [13], [14], [15], [16], [17], [18], [19], [20], [21], [22], [23], [24], [25], [26], [27], [28], [29], [30], [31], [32], [33], [34], [35], [36], [37], [38], [39], [40], [41] G-tec 29 [2], [42], [43], [7], [9], [10], [44], [45], [46], [23], [47],…”
Section: Devicesmentioning
confidence: 99%
“…[16], [18], [24], [37], [41], [42], [43], [48], [52], [53], [56], [59], [62], [64], [69], [74], [76], [82], [83], [88], [91], [94], [95], [100], [101], [111], [116], [133] Assistance 11 These articles show how different technologies can help assist patients with neurological disorders and in daily life procedures.…”
Section: F Classification Of Articles By Application Domain/ Fieldmentioning
confidence: 99%