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.
Broad Learning System [1] proposed recently demonstrates efficient and effective learning capability. This model is also proved to be suitable for incremental learning algorithms by taking the advantages of random vector flat neural networks. In this paper, a modified BLS structure based on the K-means feature extraction is developed. Compared with the original broad learning system, acceptable performance...
This paper proposes a novel feature fusion method for the protein subcellular multiple-site localization prediction. Several types of features are employed in this novel protein coding method. The first one is the composition of amino acids. The second is pseudo amino acid composition, which mainly extract the location information of each amino acid residues in protein sequence. Lastly, the information...
Various modeling methodologies have been proposed to model the human face realistically. However, despite the fact that these methods can give high-quality results, the time, cost, and labor required to generate such models by these methods are often high. In this paper, we propose an integrated modeling approach combining Shape-From-Shading (SFS) and Local Morphable Model (LMM), which can rapidly...
Ultrasound imaging has been widely used to investigate the morphological changes during skeletal muscle contraction. In this study, the ultrasound images were recorded from extensor muscle during finger flexion, and the optical flow algorithm was used to recognize the muscle deformation for different fingers' flexions. The preliminary results demonstrated that the directions of optical flow and deformation...
We propose a feature extraction method based on the Volterra autoregressive model's prediction power and the data's predictability for the EEG signals to automatically detect the epileptic EEG signals from the EEG recordings. The method of determining the embedding dimension based on nonlinear prediction is applied to choose the embedding dimension of the EEG data. The proposed feature extraction...
In this paper, a new approach using independent component analysis (ica) and hybrid Flexible Neural Tree (FNT) is put forward for face recognition. To improve the quality of the face images, a series of image pre-processing techniques, which include histogram equalization, edge detection and geometrical transformation are used. The ICA based on Kernel principal component analysis (KPCA) and FastICA...
The electroencephalogram (EEG) is a set of data measured by electrodes placed on the scalp and is often under the influences of artifacts. Mental EEG is recorded when a person performs different mental tasks. In this article, we separated the mental EEG signals into independent components with individual meanings based on independent component analysis (ICA) method, and the EEG was reconstructed by...
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.