Functional neuroimaging has increased our understanding of human brain function tremendously and has become a standard tool in clinical and cognitive neuroscience research. We briefly review its methodological foundations and describe remaining challenges for translational research. The application of neuroimaging results to individual subjects, for example in predicting treatment response or d...

Current stereo algorithms are capable to calculate accurate (as defined, e.g., by needs in vision-based driver assistance) dense disparity maps in real time. They have become the source of three-dimensional data for several indoor and outdoor applications. However, ground truthbased evaluation of such algorithms has been typically limited to data sets generated indoors in laboratories. In this ...

A special multilayer percep tron architecture known as FuNe I is suc cessfully used for generating fuzzy systems for a number of real world applications The FuNe I trained with supervised learn ing can be used to extract fuzzy rules from a given representative input output data set Furthermore optimization of the knowledge base is possible including the tuning of membership functions The new me...

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The potential of compressive sensing (CS) has spurred great interest in the research community and is a fast growing area of research. However, research translating CS theory into practical hardware and demonstrating clear and significant benefits with this hardware over current, conventional imaging techniques has been limited. This article helps researchers to find those niche applications wh...

Face recognition is one of the most challenging problems of computer vision and pattern recognition. The difficulty in face recognition arises mainly from facial appearance variations caused by factors, such as expression, illumination, partial face occlusion, and time gap between training and testing data capture. Moreover, the performance of face recognition algorithms heavily depends on prio...

This paper describes two characteristics of language specification tools that support their use at scales beyond small prototypes. First is the ability to both explicitly and implicitly (via translation) specify the semantics of language constructs. In attribute grammars this achieved by forwarding and is used to specify languages by building features on top of a smaller core language. Second i...

In this paper, we learn to discover composite operators and features that are evolved from combinations of primitive image processing operations to extract regions-of-interest (ROIs) in images. Our approach is based on genetic programming (GP). The motivation for using GP is that there are a great many ways of combining these primitive operations and the human expert, limited by experience, kno...

This paper introduces a next generation software-based GPS receiver technology that is capable of providing meters level accuracy, independent raw measurements and PVT (position, velocity, time) solutions using as little as 1-2ms (millisecond) of I/Q samples. This unprecedented performance is based on a revolutionary patent pending technology called Deep-RTM. Unlike conventional software based ...

Over the last decade, numerous papers have presented the use of dry electrodes capable of acquiring electroencephalogram (EEG) signals through hair. A few of these dry electrode prototypes have even progressed from labbased EEG acquisition to commercial sales. While the field has improved rapidly as of late, most dry electrodes share a number of shortcomings that limit their potential real worl...