1. A method comprising: obtaining, by at least one computing device, input data that is a set of training inputs for a convolutional neural network, the convolutional neural network including multiple layers, one of the multiple layers including a convolution layer, the convolution layer including one or more filters; training, by the at least one computing device, the convolutional neural network based on the set of training inputs; binarizing, by the at least one computing device, the convolution layer by converting parameters of the one or more filters from floating point to binary values; generating, by the at least one computing device, look-up table values of a look-up table for the binary values, the look-up table storing pre-computed results that are possible for the convolution layer; and outputting, by the at least one computing device, a result of the generating.