Machine learning approaches are increasingly used to extract patterns and insights from the ever-increasing stream of geospatial data, but current approaches may not be optimal when system behaviour is dominated by spatial or temporal context. Here, ...
Face recognition is a natural skill that a child performs from the first days of life; unfortunately, there are people with visual or neurological problems that prevent the individual from performing the process visually. This work describes a system...
Face recognition using a single reference image per subject is challenging, above all when referring to a large gallery of subjects. Furthermore, the problem hardness seriously increases when the images are acquired in unconstrained conditions. In th...
Proceedings of the National Academy of Sciences of the United States of America
Dec 17, 2018
Despite significant recent progress, machine vision systems lag considerably behind their biological counterparts in performance, scalability, and robustness. A distinctive hallmark of the brain is its ability to automatically discover and model obje...
In order to solve the problem of face recognition in complex environments being vulnerable to illumination change, object rotation, occlusion, and so on, which leads to the imprecision of target position, a face recognition algorithm with multi-featu...
Coarse-to-fine theories of vision propose that the coarse information carried by the low spatial frequencies (LSF) of visual input guides the integration of finer, high spatial frequency (HSF) detail. Whether and how LSF modulates HSF processing in n...
Face recognition is a computationally challenging task that humans perform effortlessly. Nonetheless, this remarkable ability is better for familiar faces than unfamiliar faces. To account for humans' superior ability to recognize familiar faces, cur...
Inspired by the primate visual system, deep convolutional neural networks (DCNNs) have made impressive progress on the complex problem of recognizing faces across variations of viewpoint, illumination, expression, and appearance. This generalized fac...
IEEE transactions on neural networks and learning systems
Jun 5, 2018
This paper deals with sparse signal reconstruction by designing a discrete-time projection neural network. Sparse signal reconstruction can be converted into an L -minimization problem, which can also be changed into the unconstrained basis pursuit d...
Faces convey rich information including identity, gender and expression. Current neural models of face processing suggest a dissociation between the processing of invariant facial aspects such as identity and gender, that engage the fusiform face are...