Premium Access to Convolutional Neural Networks

Neural Networks (NNs) are today used for all our daily tasks; for instance, in mobile phones. We here want to show how to restrict their access to privileged users. Our solution relies on a degraded implementation which can be corrected thanks to a PIN. We explain how to select a few parameters in an NN so as to maximize the gap in the accuracy between the premium and the degraded modes. We report experiments on an implementation of our proposal on a deep NN to prove its practicability.

New Algorithmic Approaches to Point Constellation Recognition

Point constellation recognition is a common problem with many pattern matching applications. Whilst useful in many contexts, this work is mainly motivated by fingerprint matching. Fingerprints are traditionally modelled as constellations of oriented points called minutiae. The fingerprint verifier's task consists in comparing two point constellations. The compared constellations may differ by rotation and translation or by much more involved transforms such as distortion or occlusion. This paper presents three new constellation matching algorithms. The first two methods generalize an algorithm by Bringer and Despiegel. Our third proposal creates a very interesting analogy between mechanical system simulation and the constellation recognition problem.