A Study and Comparison of Human and Deep Learning Recognition Performance under Visual Distortions

• Published in: 2017 26th International Conference on Computer Communication and Networks (ICCCN) pp. 1 - 7
• Main Authors: Dodge, Samuel, Karam, Lina
• Format: Conference Proceeding
• Language: English; Japanese
• Published: IEEE 01.07.2017
• Subjects: Distortion; Neural networks; Robustness; Testing; Training; Visual systems

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, a...