Question: ) Layer 1: convolutional layer with the ReLU nonlinear activiationfunction, 100 55 filters with stride 1.2) Layer 2: 22 max-pooling layer3) Layer 3: convolutional layer

) Layer 1: convolutional layer with the ReLU nonlinear activiationfunction, 100 55 filters with stride 1.2) Layer 2: 22 max-pooling layer3) Layer 3: convolutional layer with the ReLU nonlinear activiationfunction, 50 33 filters with stride 1.4) Layer 4: 22 max-pooling layer5) Layer 5: fully-connected layer6) Layer 6: classfication layer How many model parameters we need to optimise in the first layerand in the second layer (assume the bias term is used) (4 pointsand 4 points)

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