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We propose an ensemble approach for multi-target binary classification, where the target class breaks down into a disparate set of pre-defined target-types. The system goal is to maximize the probability of alerting on targets from any type while excluding background clutter. The agent-classifiers that make up the ensemble are binary classifiers tr   ...more

Revolutionizing Prosthetics is a government-sponsored program focused on maturing the many foundational technologies that comprise neural prosthetic systems. Targeting the needs of amputees and movement-impaired individuals, the program focused on technological advancements in areas such as advanced neural recording devices, neural decoding and enc   ...more

Neurobiological theories of spatial cognition developed with respect to recording data from relatively small and/or simplistic environments compared to animals' natural habitats. It has been unclear how to extend theoretical models to large or complex spaces. Complementarily, in autonomous systems technology, applications have been growing for   ...more

This study investigates unsupervised novelty detection (ND) for screening of rare myopathies and specifically myositis. To support this study we developed from the ground up a novel and fully annotated dataset consisting of 3586 images taken of eighty nine individuals obtained under informed consent during 2016-2017. We developed and compared perfo   ...more

We present a generic data-driven method to address the problem of manipulating a three-dimensional (3-D) compliant object (CO) with heterogeneous physical properties in the presence of unknown disturbances. In this study, we do not assume a prior knowledge about the deformation behavior of the CO and type of the disturbance (e.g., internal or exte   ...more

In this paper, we investigate the use of surrogate agents to accelerate test scenario generation for autonomous vehicles. Our goal is to train the surrogate to replicate the true performance modes of the system. We create these surrogates by utilizing imitation learning with deep neural networks. By using imitator surrogates in place of the true a   ...more

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