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• W4313444672 abstract "Cognitive load is used in the field of psychology to measure the performance of humans while performing different mental tasks that engages perception, attention, learning, memory, comprehension, and reasoning. In this paper, classification of subjects has been done as good counter or bad counter while performing mental calculations that evoke mental workload in subjects. It comes under the category of mental arithmetic or reasoning task. Electroencephalogram (EEG) signals are used as input for the classification of subjects in the above-mentioned classes using a single-layer 2 dimensional convolutional neural network (2D-CNN) model. The accuracy of the model achieved after tuning the parameters is 97.22%." @default.
• W4313444672 created "2023-01-06" @default.
• W4313444672 creator A5065486002 @default.
• W4313444672 creator A5086169494 @default.
• W4313444672 date "2023-01-01" @default.
• W4313444672 modified "2023-09-23" @default.
• W4313444672 title "Cognitive Load Classification During Arithmetic Task Using Single Convolution Layer-Based 2D-CNN Model" @default.
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• W4313444672 doi "https://doi.org/10.1007/978-981-19-5868-7_16" @default.
• W4313444672 hasPublicationYear "2023" @default.
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