O'Reilly logo

Java Deep Learning Projects by Md. Rezaul Karim

Stay ahead with the world's most comprehensive technology and business learning platform.

With Safari, you learn the way you learn best. Get unlimited access to videos, live online training, learning paths, books, tutorials, and more.

Start Free Trial

No credit card required

Pooling and padding operations

Once you understand how convolutional layers work, pooling layers are quite easy to grasp. A pooling layer typically works on every input channel independently, so the output depth is the same as the input depth. Alternatively, you may pool over the depth dimension, as we will see next, in which case the image's spatial dimensions (for example, height and width) remain unchanged, but the number of channels is reduced. Let's see a formal definition of pooling layers from TensorFlow API documentation (see more at https://github.com/petewarden/tensorflow_makefile/blob/master/tensorflow/python/ops/nn.py):

"The pooling ops sweep a rectangular window over the input tensor, computing a reduction operation for each ...

With Safari, you learn the way you learn best. Get unlimited access to videos, live online training, learning paths, books, interactive tutorials, and more.

Start Free Trial

No credit card required