to template arguments.  This way, the type of a network specifies the entire
network architecture and most of the time the user doesn't even need to do
anything with layer constructors.

variable decorator.

algorithms.

if they should be default constructed.

statements when used inside a matlab mex file.

Regression test for corellation tracker

Using float instead of double for FHOG computations

MSVC x64 SSE2 automatical support

however, that doesn't really work if we need to compute the gradients with
respect to the parameters which the layer attempted to do.  So I made the
layer's parameters non-learnable so it can continue to be inplace since the
main usecase for this layer is to be a fast replacement for bn_ during testing.

Python/Simple object detector trainer. Added upsample_limit option

Also made the bracketing phase more efficient.