Spanish Patent Application P202030060
The aim of this technology is to develop a new agnostic representation capable of removing certain sensitive information while maintaining the utility of the data. The proposed method, called SensitiveNets, can be trained for specific tasks (e.g. image classification), while minimizing the presence of selected covariates, both for the task at hand and in the information embedded in the trained network. These agnostic representations are expected to: i) improve the privacy of the data and the automatic process itself; and ii) eliminate the source of discrimination that we want to prevent
Spanish Patent Application P202030066
Most of the current CAPTCHAs have been designed to be used in a web interaction based on mouse and keyboard interfaces. Our technolgy exploite the potential of mobile devices to detect human-machine interaction. Our patented method allows to generate synthetic swipe gestures using Generative Adversarial Networks and samples acquired during real human-device interaction. This method allows to generate synthetic samples that mimic the human behaviour. BeCAPTCHA models the user behaviour in smartphone interaction using multiple inbuilt sensors.
Deformable Minutae Clustering for Latent Fingerprint Matching (2015)
Mexicant Patent MX/E/2015/016942
This patent presents a new method based on the use of clustering which is independent of the minutiae descriptors. The proposed technique improves the robustness of identification in the presence of large non-linear deformation which is associated with latent fingerprint images. The new algorithm finds multiple overlapping clusters of matching minutiae pairs which are merged together to find matching minutiae.