Several studies have demonstrated that perceiving an action influences the subsequent processing of action verbs. However, which characteristics of the perceived action are truly determinant to enable this influence is still unknown. The current stud...
Visual pattern detection and discrimination are essential first steps for scene analysis. Numerous human psychophysical studies have modeled visual pattern detection and discrimination by estimating linear templates for classifying noisy stimuli defi...
A comprehensive understanding of the stimulus-response properties of individual neurons is necessary to crack the neural code of sensory cortices. However, a barrier to achieving this goal is the difficulty of analysing the nonlinearity of neuronal r...
OBJECTIVE: Direct synthesis of speech from neural signals could provide a fast and natural way of communication to people with neurological diseases. Invasively-measured brain activity (electrocorticography; ECoG) supplies the necessary temporal and ...
IEEE transactions on neural networks and learning systems
Feb 5, 2019
Previous studies on robotic rehabilitation have shown that subjects' active participation and effort involved in rehabilitation training can promote the performance of therapies. In order to improve the voluntary effort of participants during the reh...
IEEE transactions on neural networks and learning systems
Feb 1, 2019
We present the global deep video representation learning to video-based person reidentification (re-ID) that aggregates local 3-D features across the entire video extent. Existing methods typically extract frame-wise deep features from 2-D convolutio...
The mental contents of perception and imagery are thought to be encoded in hierarchical representations in the brain, but previous attempts to visualize perceptual contents have failed to capitalize on multiple levels of the hierarchy, leaving it cha...
IEEE transactions on neural networks and learning systems
Jan 10, 2019
Driver fatigue evaluation is of great importance for traffic safety and many intricate factors would exacerbate the difficulty. In this paper, based on the spatial-temporal structure of multichannel electroencephalogram (EEG) signals, we develop a no...
Neural networks : the official journal of the International Neural Network Society
Dec 27, 2018
Graph-based embedding methods are very useful for reducing the dimension of high-dimensional data and for extracting their relevant features. In this paper, we introduce a novel nonlinear method called Flexible Discriminant graph-based Embedding with...
Deep networks provide a potentially rich interconnection between neuroscientific and artificial approaches to understanding visual intelligence, but the relationship between artificial and neural representations of complex visual form has not been el...