[{"title":"( 14 个子文件 27.42MB ) 脑电情绪识别 DEAP数据集 多种方法 CNN LSTM等","children":[{"title":"情绪分类神经网络","children":[{"title":"基于DEAP的脑电情绪识别(四分类)(五种模型作对比:一维 CNN,LSTM和二维和三维 CNN和带有LSTM的级联CNN)","children":[{"title":"Metadata_EDA.ipynb <span style='color:#111;'> 122.27KB </span>","children":null,"spread":false},{"title":"DataAugmentation","children":[{"title":"Windowing_of_Time_Series.ipynb <span style='color:#111;'> 18.77KB </span>","children":null,"spread":false}],"spread":true},{"title":"models","children":[{"title":"1DCNN_without_Windowing.ipynb <span style='color:#111;'> 620.23KB </span>","children":null,"spread":false},{"title":"Participant_Dependent_LSTM_on_DEAP.ipynb <span style='color:#111;'> 175.54KB </span>","children":null,"spread":false},{"title":"CNN_with_Symmetric_Difference_in_EEG_signals_Model_1.ipynb <span style='color:#111;'> 92.95MB </span>","children":null,"spread":false},{"title":"CNN_with_Symmetric_Difference_in_EEG_signals_Final_Model.ipynb <span style='color:#111;'> 22.82MB </span>","children":null,"spread":false},{"title":"2_level_Ensemble_of_Light_Pyramidal_1D_CNN.ipynb <span style='color:#111;'> 2.20MB </span>","children":null,"spread":false}],"spread":true},{"title":"readme.txt <span style='color:#111;'> 312B </span>","children":null,"spread":false}],"spread":true},{"title":"基于deap数据集的脑电情绪识别(2DCNN和LSTM)代码很基础","children":[{"title":"data.py <span style='color:#111;'> 1.64KB </span>","children":null,"spread":false},{"title":"model","children":[{"title":"__init__.py <span style='color:#111;'> 0B </span>","children":null,"spread":false},{"title":"eegnet.py <span style='color:#111;'> 2.71KB </span>","children":null,"spread":false},{"title":"lstm.py <span style='color:#111;'> 841B </span>","children":null,"spread":false}],"spread":true},{"title":"train.py <span style='color:#111;'> 884B </span>","children":null,"spread":false},{"title":"readme.txt <span style='color:#111;'> 47B </span>","children":null,"spread":false}],"spread":true}],"spread":true}],"spread":true}]