Apr 20, 2020 · In this study, we attempt to investigate the influence of different feature maps on the recognition performance. Six different 2D feature maps ( ...
Abstract—In recent electroencephalograph (EEG)-based emo- tion recognition, the differential entropy (DE) features extracted.
Abstract—In recent electroencephalograph (EEG)-based emo- tion recognition, the differential entropy (DE) features extracted.
EEG-based Emotion Recognition Under Convolutional Neural Network with Differential Entropy Feature Maps ... To read the full-text of this research, you can ...
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Apr 8, 2024 · [18] proposed an innovative emotion recognition model, the multitask convolutional neural network (MT-CNN), which takes brain maps generated ...
In Zheng and Lu (2015), a deep belief network is trained on differential entropy features extracted from five different frequency bands, which is proven more ...
Jun 12, 2024 · To address these issues, we have designed TPRO-NET, a neural network that takes differential entropy and enhanced differential entropy features ...
Oct 16, 2022 · [29] proposed a new multi-featured fusion network consisting of spatial and temporal neural network structures for emotion recognition with EEG ...
The step to classify emotions in EEG signals is done with Deep Convolutional Neural Network (DCNN) and Bidirectional Gated Recurrent Unit (Bi-GRU) models. The ...
This paper explored the recognition performance of three emotion recognition models: support vector machine (SVM), random forest (RF) and convolutional ...