Deep convolutional neural network for network-wide QoT estimation

We propose a novel Deep Convolutional Neural Network formulation for network-wide QoT classification tasks and show its effectiveness for networks with significant topological differences. Our formulation achieves ~99% accuracy on large and diverse test datasets.