Abstract: A method of training a neural network (NN) block for a neural network, including: performing a first quantization operation on a real-valued feature map tensor to generate a corresponding binary feature map tensor; performing a second quantization operation on a real-valued weight tensor to generate a corresponding binary weight tensor; convoluting the binary feature map tensor with the binary weight tensor to generate a convoluted output; scaling the convoluted output with a scaling factor to generate a scaled output, wherein the scaled output is equal to an estimated weight tensor convoluted with the binary feature map tensor, the estimated weight tensor corresponding to a product of the binary weight tensor and the scaling factor; calculating a loss function, the loss function including a regularization function configured to train the scaling factor so that the estimated weight tensor is guided towards the real-valued weight tensor; and updating the real-valued weight tensor and scaling factor based on th