Visualizing activations of 3D convolutional filters using keras-vis library.
| Layer (type) | Output Shape | Param |
|---|---|---|
| conv1 (Conv3D) | (None, 16, 112, 112, 64) | 5248 |
| pool1 (MaxPooling3D) | (None, 16, 56, 56, 64) | 0 |
| conv2 (Conv3D) | (None, 16, 56, 56, 128) | 221312 |
| pool2 (MaxPooling3D) | (None, 8, 28, 28, 128) | 0 |
| conv3a (Conv3D) | (None, 8, 28, 28, 256) | 884992 |
| conv3b (Conv3D) | (None, 8, 28, 28, 256) | 1769728 |
| pool3 (MaxPooling3D) | (None, 4, 14, 14, 256) | 0 |
| conv4a (Conv3D) | (None, 4, 14, 14, 512) | 3539456 |
| conv4b (Conv3D) | (None, 4, 14, 14, 512) | 7078400 |
| pool4 (MaxPooling3D) | (None, 2, 7, 7, 512) | 0 |
| conv5a (Conv3D) | (None, 2, 7, 7, 512) | 7078400 |
| conv5b (Conv3D) | (None, 2, 7, 7, 512) | 7078400 |
| zero_padding3d_2 (ZeroPadding) | (None, 2, 9, 9, 512) | 0 |
| pool5 (MaxPooling3D) | (None, 1, 4, 4, 512) | 0 |
| flatten_2 (Flatten) | (None, 8192) | 0 |
| fc6 (Dense) | (None, 4096) | 33558528 |
| dropout_3 (Dropout) | (None, 4096) | 0 |
| fc7 (Dense) | (None, 4096) | 16781312 |
| dropout_4 (Dropout) | (None, 4096) | 0 |
| fc8 (Dense) | (None, 487) | 1995239 |
Possible to use the pre-trained model in Caffe format or convert it to Keras format or simply download model weights in Keras format from here.
conv1
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