Mixed sum-product and convolutional networks for classification problems

Abstract

In this work, we propose a joint Sum-Product (SPN) and Convolutional (CNN) Network for classification problems, namely image classification performed on several real-life benchmark datasets. These mixed networks represent an original development within the probabilistic graphical models domain that outperform the traditional CNNs results.