An FPGA device receives an input matrix. A first convolutional kernel is determined by performing the exclusive nor operations between the input matrix and a first weight vector. A first binary kernel is determined based on the first convolutional kernel. A first layer feature map is determined by convoluting the input matrix using the first binary kernel. A second convolutional kernel is determined by performing the exclusive nor operations between the first feature map and the second weight vector. A pooled kernel is determined based on the second convolutional kernel. A second binary kernel is determined based on the pooled kernel. A second layer feature map is determined by convoluting the first layer feature map using the second binary kernel. A probability is determined that the input matrix is associated with a predetermined class of images. If the probability is greater than a threshold, classification results are provided.