A Study and Comparison of Human and Deep Learning Recognition Performance under Visual Distortions
A Study and Comparison of Human and Deep Learning Recognition Performance under Visual Distortions
Deep neural networks (DNNs) achieve excellent performance on standard classification tasks. However, under image quality distortions such as blur and noise, classification accuracy becomes poor. In this work, we compare the performance of DNNs with human subjects on distorted images. We show that, although DNNs perform better than or on …