Hands-On Convolutional Neural Networks with TensorFlow

Conversion from traditional CNN to Fully Convnets

Something very important to efficient object detectors, that improves the reuse of computation, is to use sliding windows convolutionally. In order to this,we will convert all FC layers to CONV layers, as shown in the next figure.

The purpose of implementing our network this way is that they can use a bigger image as input than what they are originally designed for and at the same time share computations to make it all more efficient. The name of this type of network, where all the FC layers are converted to CONV layers, is called fully convolutional network (FCN).

The basic technique to convert an FC layer to a CONV layer is to use the kernel size as big as the input spatial dimensions and ...