Understanding convolutional neural network classification errors caused by image quality degradation

Robustness to image quality degradations is critical for developing Convolutional Neural Networks (CNNs) for real-world image classification. This paper advances previous analysis of how optical aberrations and optical scatter degrade classification performance by exploring how they cause classification errors to manifest within CNN layers.