The Infona portal uses cookies, i.e. strings of text saved by a browser on the user's device. The portal can access those files and use them to remember the user's data, such as their chosen settings (screen view, interface language, etc.), or their login data. By using the Infona portal the user accepts automatic saving and using this information for portal operation purposes. More information on the subject can be found in the Privacy Policy and Terms of Service. By closing this window the user confirms that they have read the information on cookie usage, and they accept the privacy policy and the way cookies are used by the portal. You can change the cookie settings in your browser.
The iterative closest point (ICP) algorithm is fast and accurate for rigid point set registration, but it works badly when there are many outliers and noises in the point sets. This paper instead proposes a novel method based on the ICP algorithm to deal with this problem. Firstly, correntropy is introduced into the rigid registration problem and then a new energy function based on maximum correntropy...
Working memory (WM) is particularly important for higher cognitive tasks. Previous studies have shown that there are several brain networks under WM task or training, however, it is still unknown how many networks are involved in WM. In this paper, we utilize the method of modularity in the graph theory to explore the module distribution and the degree of coupling of the brain network under the real-time...
Smart video analysis is attracting increasing attention with the pervasive use of surveillance camera. In this paper, we address video anomaly detection by Uniform Local Gradient Pattern based Optical Flow (ULGP-OF) descriptor and one-class extreme learning machine (OCELM). Using the proposed ULGP-OF descriptor, we naturally combine the robust 2D image texture descriptor LGP with video optical flow...
In this paper, we present a sparse hierarchical non-parametric Bayesian (SHNB) model, which is used to represent the data captured by the light field cameras. Specifically, a light field can be represented as a set of sub-aperture views. In order to capture the visual variations of these viewpoints, we propose the so-called “depth flow” features. Then based on the depth flow features, we model these...
A structured 3D SOM is an extension of a Self-Organizing Map from 2D to 3D in such a way that a pre-defined structure is built into the design of the 3D map. The structured 3D SOM is a 3×3×3 structure that has a distinct core cube in the center and exterior cubes around the core. The current application of the structured SOM, as a digital music archive, only uses the 8 corner cubes among the 26 exterior...
Fundamental challenges and goals of the cognitive algorithms are moving super-intelligent machines and super-intelligent humans from dreams to reality. This paper is devoted to a technical way to reach some specific aspects of super-intelligence that are beyond the current human cognitive abilities. Specifically the proposed technique is to overcome inabilities to analyze a large amount of abstract...
During the last few years, Convolutional Neural Networks are slowly but surely becoming the default method solve many computer vision related problems. This is mainly due to the continuous success that they have achieved when applied to certain tasks such as image, speech, or object recognition.
EEG is one the most effective tools used in the diagnosis of epilepsy. However, proper diagnosis of epilepsy requires the detection and analysis of epileptic seizures for a long period of time. Manual monitoring of long term EEG is tedious and costly. Therefore, a reliable automated seizure detection system is desirable. Most current state-of-the-art methods use hand crafted feature extraction and...
Restricted Boltzmann Machine (RBM) is an important generative model modeling vectorial data. While applying an RBM in practice to images, the data have to be vectorized. This results in high-dimensional data and valuable spatial information has got lost in vectorization. In this paper, a Matrix-Variate Restricted Boltzmann Machine (MVRBM) model is proposed by generalizing the classic RBM to explicitly...
Human activity recognition involves classifying times series data, measured at inertial sensors such as accelerometers or gyroscopes, into one of pre-defined actions. Recently, convolutional neural network (CNN) has established itself as a powerful technique for human activity recognition, where convolution and pooling operations are applied along the temporal dimension of sensor signals. In most...
L1-norm maximization based Discriminant Locality Preserving Projection (DLPP-L1) is shown to be effective and robust to the outliers in given data, but DLPP-L1 is based on the vector space, so it has to convert those 2D matrices into high-dimensional 1D vectorized representations when handing images. But such transformation usually destroys the topology structures of images pixels, which can decrease...
Many processes in nature display quasi-periodic behavior, including variable stars in distant galaxies and oscillations in brains. In this work we model quasi-periodic lightcurves using neuropercolation, which describes complex spatio-temporal oscillations arising from random cellular automata near criticality. We show that neuropercolation is able to model lightcurves from various stars of the gamma-Doradus...
Alzheimer's disease as one type of dementia can cause problems to human memory, thinking and behavior. The brain damage can be detected using brain volume and whole brain form. The correlation between brain shrinkage and reduction of brain volume can affect to deformation texture. In this research, the enhancement texture approach was proposed, called advanced local binary pattern (ALBP) method. ALBP...
Set the date range to filter the displayed results. You can set a starting date, ending date or both. You can enter the dates manually or choose them from the calendar.