Positive and negative max pooling for image classification

Max pooling has been regard as the best pooling method in image classification when image features are coded by sparse coding ^[2]. However, max pooling reduces the classification discrimination, since it doesn´t distinguish the sign of coding coefficient but only selects the max absolute value. In order to increase the image representation discrimination, we preserve the sign of code coefficient and develop a feature pooling method named PN-Max pooling. Experimental results show that PN-Max pooling achieves higher image classification accuracy than Max pooling.