CODEWITHSUNDEEP
deep-learningconv-neural-network
Yoda
Yoda

Reputation: 23

Data Flow in CNN

What would be the output of a network with 32 units in 1st convolutional layer followed by a pooling layer with stride=2 and k=2 followed by another convolutional layer with 64 units followed by another pooling layer with stride = 2 and k=2 , input image dimensions are 28*28*1

Upvotes: 0

Views: 258

Answers (1)

hola
hola

Reputation: 612

I will assume that you are using same padding in each convolution, then the output of you model will be of shape (7, 7, 64). You can use a code similar to this one in keras if you don't want to compute the size by hand:

from keras.models import Sequential
from keras.layers import Conv2D, MaxPooling2D

model = Sequential()
model.add(Conv2D(32, 3, padding="same", input_shape=(28, 28, 1)))
model.add(MaxPooling2D(2, 2))
model.add(Conv2D(64, 3, padding="same"))
model.add(MaxPooling2D(2, 2))

print(model.summary())

Upvotes: 1

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