Gerardo Rivera
Add weights and results for model without the classification output
3f65c3f

Model: "model_2" __________________________________________________________________________________________________ Layer (type) Output Shape Param # Connected to

input_data (InputLayer) [(None, 4, 3, 24, 7 0 []
2)]

conv3d_6 (Conv3D) (None, 36, 1, 24, 7 13860 ['input_data[0][0]']
2)

max_pooling3d_4 (MaxPooling3D) (None, 36, 1, 12, 3 0 ['conv3d_6[0][0]']
6)

conv3d_7 (Conv3D) (None, 36, 1, 12, 3 31140 ['max_pooling3d_4[0][0]']
6)

max_pooling3d_5 (MaxPooling3D) (None, 36, 1, 6, 18 0 ['conv3d_7[0][0]']
)

conv3d_8 (Conv3D) (None, 36, 1, 6, 18 31140 ['max_pooling3d_5[0][0]']
)

flatten_2 (Flatten) (None, 3888) 0 ['conv3d_8[0][0]']

dense1 (Dense) (None, 50) 194450 ['flatten_2[0][0]']

dense2 (Dense) (None, 50) 2550 ['dense1[0][0]']

eoutput (Dense) (None, 12) 612 ['dense2[0][0]']

coutput (Dense) (None, 12) 612 ['dense2[0][0]']

time (Dense) (None, 2) 102 ['dense2[0][0]']

Total params: 274,466 Trainable params: 274,466 Non-trainable params: 0