nirs4all.operators.models.tensorflow.legacy.inception_1d_cnn module
Inception 1D_CNN Models in Tensorflow-Keras. References - Inception_v1 (GoogLeNet): https://arxiv.org/abs/1409.4842 [Going Deeper with Convolutions] Inception_v2: http://arxiv.org/abs/1512.00567 [Rethinking the Inception Architecture for Computer Vision] Inception_v3: http://arxiv.org/abs/1512.00567 [Rethinking the Inception Architecture for Computer Vision] Inception_v4: https://arxiv.org/abs/1602.07261 [Inception-v4, Inception-ResNet and the Impact of Residual Connections on Learning]
- nirs4all.operators.models.tensorflow.legacy.inception_1d_cnn.Conv_1D_Block(x, model_width, kernel, strides=1, padding='same')[source]
- nirs4all.operators.models.tensorflow.legacy.inception_1d_cnn.Inception_Module_A(inputs, filterB1_1, filterB2_1, filterB2_2, filterB3_1, filterB3_2, filterB3_3, filterB4_1, i)[source]
- nirs4all.operators.models.tensorflow.legacy.inception_1d_cnn.Inception_Module_B(inputs, filterB1_1, filterB2_1, filterB2_2, filterB3_1, filterB3_2, filterB3_3, filterB4_1, i)[source]
- nirs4all.operators.models.tensorflow.legacy.inception_1d_cnn.Inception_Module_C(inputs, filterB1_1, filterB2_1, filterB2_2, filterB3_1, filterB3_2, filterB3_3, filterB4_1, i)[source]
- nirs4all.operators.models.tensorflow.legacy.inception_1d_cnn.Inceptionv1_Module(inputs, filterB1_1, filterB2_1, filterB2_2, filterB3_1, filterB3_2, filterB4_1, i)[source]
- nirs4all.operators.models.tensorflow.legacy.inception_1d_cnn.Inceptionv2_Module(inputs, filterB1_1, filterB2_1, filterB2_2, filterB3_1, filterB3_2, filterB3_3, filterB4_1, i)[source]
- nirs4all.operators.models.tensorflow.legacy.inception_1d_cnn.Reduction_Block_A(inputs, filterB1_1, filterB1_2, filterB2_1, filterB2_2, filterB2_3, i)[source]
- nirs4all.operators.models.tensorflow.legacy.inception_1d_cnn.Reduction_Block_B(inputs, filterB1_1, filterB1_2, filterB2_1, filterB2_2, filterB2_3, i)[source]