Recognising fake images using frequency analysis

EurekAlert  July 16, 2020 To date, deep-fake images have been analysed using complex statistical methods. Researchers in Germany converted the images into the frequency domain using the discrete cosine transform and express the image as the sum of many different cosine functions. Natural images consist mainly of low-frequency functions. The analysis has shown that images generated by GANs (Generative Adversarial Networks) exhibit artefacts in the high-frequency range. The researchers’ experiments showed that these artefacts do not only occur in GAN generated images. They are a structural problem of all deep learning algorithms. Frequency analysis is therefore an effective way to […]

New program picks out targets in a crowd quickly and efficiently

Phys. org  February 22, 2019 Previous work on visual search has focused on searching for perfect matches of a target after extensive category-specific training. An international team of researchers (Singapore, USA – University of Minnesota) shows that humans can efficiently and invariantly search for natural objects in complex scenes. They developed a biologically inspired computational model that can locate targets without exhaustive sampling and generalize to novel objects. They trained the model to look for something that had similar features to the example image of a dog. This enabled the model to generalize from a single dog image, to the […]