Multi-Channel Cross Modal Detection of Synthetic Face Images

Synthetically generated face images have shown to be indistinguishable from real images by humans and as such can lead to a lack of trust in digital content as they can, for instance, be used to spread misinformation. Therefore, the need to develop algorithms for detecting entirely synthetic face images is apparent. Of interest are images generated by state-of-the-art deep learning-based models, as these exhibit a high level of visual realism. Recent works have demonstrated that detecting such synthetic face images under realistic circumstances remains difficult as new and improved generative models are proposed with rapid speed and arbitrary image post-processing can be applied. In this work, we propose a multi-channel architecture for detecting entirely synthetic face images which analyses information both in the frequency and visible spectra using Cross Modal Focal Loss. We compare the proposed architecture with several related architectures trained using Binary Cross Entropy and show in cross-model experiments that the proposed architecture supervised using Cross Modal Focal Loss, in general, achieves most competitive performance

A New Biometric Template Protection using Random Orthonormal Projection and Fuzzy Commitment

Biometric template protection is one of most essential parts in putting a biometric-based authentication system into practice. There have been many researches proposing different solutions to secure biometric templates of users. They can be categorized into two approaches: feature transformation and biometric cryptosystem. However, no one single template protection approach can satisfy all the requirements of a secure biometric-based authentication system. In this work, we will propose a novel hybrid biometric template protection which takes benefits of both approaches while preventing their limitations. The experiments demonstrate that the performance of the system can be maintained with the support of a new random orthonormal project technique, which reduces the computational complexity while preserving the accuracy. Meanwhile, the security of biometric templates is guaranteed by employing fuzzy commitment protocol.Comment: 11 pages, 6 figures, accepted for IMCOM 201

Context-based texture analysis for secure revocable iris-biometric key generation

In this work we present an iris-biometric cryptosystem. Based on the idea of exploiting the most reliable components of iriscodes, cryptographic keys are extracted, long enough to be applied in common cryptosystems. The main benefit of our system is that cryptographic keys are directly derived from biometric data, thus, neither plain biometric data nor encrypted biometric data has to be stored in templates. Yet, we provide fully revocable cryptographic keys. Experimental results emphasize the worthiness of our approach

Устройство для перемещения датчиков в магнитном поле малогабаритного бетатрона

Рассматривается возможность увеличения точности измерений характеристик магнитного поля посредством более точной установки датчиков в исследуемой точке

Prolactin

During an oral glucose tolerance test (OGTT) glucose and insulin levels were measured in 26 patients with prolactin-producing pituitary tumours without growth hormone excess. Basal glucose and insulin levels did not differ from the values of an age-matched control group. After glucose load the hyperprolactinaemic patients showed a decrease in glucose tolerance and a hyperinsulinaemia. Bromocriptine (CB 154), which suppressed PRL, improved glucose tolerance and decreased insulin towards normal in a second OGTT. — Human PRL or CB 154 had no significant influence on insulin release due to glucose in the perfused rat pancreas. — These findings suggest a diabetogenic effect of PRL. CB 154 might be a useful drug in improving glucose utilization in hormone-active pituitary tumours

Research in graphic design

An invited and reviewed opinion piece about the current state of research in graphic/communication design

On the use of fingernail images as transient biometric identifiers

The significant advantages that biometric recognition technologies offer are in danger of being left aside in everyday life due to concerns over the misuse of such data. The biometric data employed so far focuses on the permanence of the characteristics involved. A concept known as ‘the right to be forgotten’ is gaining momentum in international law and this should further hamper the adoption of permanent biometric recognition technologies. However, a multitude of common applications are short-term and, therefore, non-permanent biometric characteristics would suffice for them. In this paper we discuss ‘transient biometrics,’ i.e. recognition via biometric characteristics that will change in the short term and show that images of the fingernail plate can be used as a transient biometric with a useful life-span of less than 6 months. A direct approach is proposed that requires no training and a relevant evaluation dataset is made publicly available