CNN Convolutional Layer Operations 3

Question 1

What is the receptive field of a neuron in the output of a convolutional layer?

Accepted Answer

The region of the input that influences that neuron's activation

Answer

The receptive field is the spatial region in the input (or previous feature map) that a given output neuron 'sees' and is influenced by.

Question 2

How does increasing filter size (e.g., from 3×3 to 7×7) affect the receptive field of a single convolutional layer?

Accepted Answer

Larger receptive field per layer

Answer

A larger filter directly covers more spatial area of the input, increasing the receptive field of each output neuron in that layer.

Question 3

In a depthwise separable convolution, what does the depthwise step do?

Accepted Answer

Applies a separate filter to each input channel independently

Answer

The depthwise step convolves each input channel with its own dedicated spatial filter, keeping channels separate.

Question 4

What is the output depth (number of channels) when 128 filters are applied to a 64-channel input?

Accepted Answer

128

Answer

The output depth always equals the number of filters, regardless of the input channel count.

Question 5

Which padding strategy discards border activations and produces a smaller output than the input (with stride=1)?

Accepted Answer

Valid padding

Answer

Valid (no) padding does not add zeros, so the filter cannot center on border pixels, shrinking the output.

CNN - Convolutional Neural Networks Practice Test