{ }
View source on GitHub |
Computes a 3-D convolution given 5-D input
and filters
tensors.
tf.nn.conv3d(
input,
filters,
strides,
padding,
data_format='NDHWC',
dilations=None,
name=None
)
In signal processing, cross-correlation is a measure of similarity of two waveforms as a function of a time-lag applied to one of them. This is also known as a sliding dot product or sliding inner-product.
Our Conv3D implements a form of cross-correlation.
Returns | |
---|---|
A Tensor . Has the same type as input .
|