As the early stage of Alzheimer's disease (AD), mild cognitive impairment (MCI) has high chance to convert to AD. Effective prediction of such conversion from MCI to AD is of great importance for early diagnosis of AD and also for evaluating AD risk ...
A neuro-inspired computing paradigm beyond the von Neumann architecture is emerging and it generally takes advantage of massive parallelism and is aimed at complex tasks that involve intelligence and learning. The cross-point array architecture with ...
IEEE transactions on pattern analysis and machine intelligence
Oct 1, 2015
This paper introduces a spiking hierarchical model for object recognition which utilizes the precise timing information inherently present in the output of biologically inspired asynchronous address event representation (AER) vision sensors. The asyn...
IEEE transactions on pattern analysis and machine intelligence
Oct 1, 2015
Active learning techniques have gained popularity to reduce human effort in labeling data instances for inducing a classifier. When faced with large amounts of unlabeled data, such algorithms automatically identify the exemplar instances for manual a...
IEEE transactions on pattern analysis and machine intelligence
Oct 1, 2015
A significant body of literature on saliency modeling predicts where humans look in a single image or video. Besides the scientific goal of understanding how information is fused from multiple visual sources to identify regions of interest in a holis...
The Journal of the Acoustical Society of America
Sep 1, 2015
The problem of nonlinear acoustic to articulatory inversion mapping is investigated in the feature space using two models, the deep belief network (DBN) which is the state-of-the-art, and the general regression neural network (GRNN). The task is to e...
IEEE transactions on pattern analysis and machine intelligence
Sep 1, 2015
Existing deep convolutional neural networks (CNNs) require a fixed-size (e.g., 224 × 224) input image. This requirement is "artificial" and may reduce the recognition accuracy for the images or sub-images of an arbitrary size/scale. In this work, we ...
Journal of the Optical Society of America. A, Optics, image science, and vision
Aug 1, 2015
The Cramér-Rao lower bound (CRLB) is a valuable tool to quantify fundamental limits to estimation problems associated with imaging systems, and has been used previously to study image registration performance bounds. Most existing work, however, assu...
The Journal of the Acoustical Society of America
Aug 1, 2015
This research aims to explore the feasibility of using back-propagation (BP) neural networks and electroencephalograms (EEGs) to recognize the emotional reactions induced by sound stimuli in the dimensions of pleasure and arousal, as well as compare ...
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