The architecture is for binary image classification. Input image layer with zerocenter nomalisation and a input of size 50x275x3 Convolution2dlayer with a filter size of 25x138, 6 filters and a stride of 13x69 and padding "same" Batch normalisation layer ReLU layer...
It turns out that the most efficient way to spend the symmetry is to achieve the normalisation of being a nonnegative real; this is of course possible since any complex number can be turned into a nonnegative real by multiplying by an appropriate phase . Once is a nonnegative real, the ...
This velocity can be of four types: batch or interval, near time or nearly time, which is almost real time, real-time, and streaming. As can be seen, this “V” has two types of velocities, the one of reading or content creation and the one of processing, which can be independent ...