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.
We present a new automated onset detection approach for behavioral tasks of patients with Parkinson's disease (PD) using Local Field Potential (LFP) signals collected during Deep Brain Stimulation (DBS) implantation surgeries. Using time-frequency signal processing methods, features are extracted and clustered in the feature space. A supervised Discrete Hidden Markov Models (DHMM) is employed and...
We propose adaptive learning methods for identifying different behavioral tasks of patients with Parkinson's disease (PD). The methods use local field potential (LFP) signals that were collected during Deep Brain Stimulation (DBS) implantation surgeries. Using time-frequency signal processing methods, features are first extracted and then clustered in the feature space using two different methods...
Automatic detection of spontaneous facial Action Units (AUs) in video has many applications including understanding infants' emotion-mediated interactions and development. The target AUs for detection are those essential to positive and negative emotion (i.e., AU 6, AU 12, and AU 20). Tracking and extraction of facial features is especially challenging in infants. Face shape and texture markedly differ...
The steganographic method named Tri-way Pixel Value Differencing (TPVD) which is a modified version of original Pixel Value Differencing (PVD) steganography, has significantly improved the embedding capacity of original method by embedding secret bits in all horizontal, vertical and diagonal edges of cover images. However, we have shown in this paper that TPVD is drastically vulnerable to statistical...
Pixel value differencing (PVD) is a steganographic method which embeds secret data in images based on spatial information. PVD has relatively high capacity but its effectiveness has been questioned by variety of steganalysis attacks. These attacks use the difference histogram quantization to reveal existence of secret data in a stego image. In this paper, we propose some modifications to PVD method...
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.