Assertion: neural network's layer | /r/CapableOf | downsample the input
Facets:
value: each time
type: TEMPORAL
value: spatially
type: MANNER
value: by a factor of two
type: OTHER
Source sentences:
text: Consider a ConvNet architecture that takes a 224x224x3 image, and then uses a series of CONV layers and POOL layers to reduce the image to an activations volume of size 7x7x512 (in an AlexNet architecture that we’ll see later, this is done by use of 5 pooling layers that downsample the input spatially by a factor of two each time, making the final spatial size 224/2/2/2/2/2 = 7).