CNN-LSTM architecture. (None, 150, 6, 3) in the input layer specifies that the CNN model can accept input data with variable batch sizes (None), where each sample has a length of 150 elements (fixed size input vector), a height of 6 rows (number of samples), and a width of 3 columns (number of channels). The Lambda layer is used to adjust the shape of the output from the CNN layer to input for the LSTM layer.
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https://figshare.com/articles/dataset/CNN-LSTM_architecture_None_150_6_3_in_the_input_layer_specifies_that_the_CNN_model_can_accept_input_data_with_variable_batch_sizes_None_where_each_sample_has_a_length_of_150_elements_fixed_size_input_vector_a_height_of_6_rows_number_of_samp/29799672
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CNN-LSTM architecture. (None, 150, 6, 3) in the input layer specifies that the CNN model can accept input data with variable batch sizes (None), where each sample has a length of 150 elements (fixed size input vector), a height of 6 rows (number of samples), and a width of 3 columns (number of channels). The Lambda layer is used to adjust the shape of the output from the CNN layer to input for the LSTM layer.
创建时间：
2025-08-01
