  We propose a novel universal detector for detecting images generated by using
CNNs. In this paper, properties of checkerboard artifacts in CNN-generated
images are considered, and the spectrum of images is enhanced in accordance
with the properties. Next, a classifier is trained by using the enhanced
spectrums to judge a query image to be a CNN-generated ones or not. In
addition, an ensemble of the proposed detector with emphasized spectrums and a
conventional detector is proposed to improve the performance of these methods.
In an experiment, the proposed ensemble is demonstrated to outperform a
state-of-the-art method under some conditions.
