Depth of a network
The number of layers in the network.
Feature vector / representation / volume
A three dimensional tensor of size
obtained in a certain layer of a neural network.
W is the width, H is the height and D is the depth, i.e., the number of channels.
If there is more than one example, this becomes a four dimensional tensor of size
, where
is the batch size.
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Spatial invariant feature vector
A feature vector that remains unchanged even if the input to the network is spatially translated.
Filters and biases
Filters are a four dimensional tensor of size
and biases are a vector of length
.
is the width and height of the filter,
is the number of channels and
is the number of filters.
Neighbourhood
A group of consecutive entries in a two-dimensional signal that has a rectangular or a square shape. image source