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.
Over 50 million persons worldwide are affected by epilepsy. Epilepsy is a brain disorder known for sudden, unexpected transitions from normal to pathological behavioral states called epileptic seizures. Epilepsy poses a significant burden to society due to associated healthcare cost to treat and control the unpredictable and spontaneous occurrence of seizures. There is a need for a quick screening...
Vehicle Tracking and positioning in GSM networkwith greater accuracy is one of the major popular research topics of Intelligence transportation System and it pass on with the evolution of techniques and methods which enable the data processor to learn and execute activities with the help of Machine learning. Support Vector Machine (SVM) is an isolated classifier which deals with both linear and nonlinear...
Large imbalanced datasets have introduced difficulties to classification problems. They cause a high error rate of the minority class samples and a long training time of the classification model. Therefore, re-sampling and data size reduction have become important steps to pre-process the data. In this paper, a sampling strategy over a large imbalanced dataset is proposed, in which the samples of...
High Efficiency Video Coding (HEVC) achieves high efficiency by introducing a new coding structure in adoption of coding unit (CU), prediction unit (PU) and transform unit (TU). However, it also imposes great computation burden on the mode decision of encoders. In this paper, we propose a fast CU depth decision scheme to reduce the encoder complexity for HEVC. Firstly, the relationship between rate-distortion...
Good body posture is important because it helps to reduce the risk of musculoskeletal injuries and permanent distortions which may interfere with efficient functioning of the body. Individuals need to be aware that good body posture is vital for a healthy quality of life, especially as one ages. However, an individual's ability to detect poor posture can be difficult as a faulty posture tends to feel...
This paper tries to study the issues and challenges for developing a Named Entity Recognition (NER) system for a resource scarce language of north east India. Kokborok a language spoken in the state of Tripura is taken as the target language in developing our NER system. Kokborok is an under resource language and not much digital work is available. We have used the frequency based approach to test...
Fuzzy c-regression models (FCRM) give us multiple clusters and regression models of each cluster simultaneously, while support vector regression models (SVRM) involve kernel methods which enable us to analyze non-linear structure of the data. We combine these two concepts and propose the united fuzzy c-support vector regression models (FC-SVRM). In case that c is unknown, we introduce sequential regression...
Massive user generated content (UGC) videos are produced each day on the Internet. These videos have become a very important integrant in existing social networking services (SNS). However, unlike professional films, the content of UGC videos is usually unstructured and lacks contextual annotation for management. The motivation behind Huawei Accurate and Fast Mobile Video Annotation Challenge (MoVAC)...
In order to solve the two-dimensional code image tilt problem which affects locating the image, establishing and identifying sampling network, we suggest a two-dimensional image tilt correction method. In the proposed method, the least squares support vector machine (SVM) is used to regress the pixel coordinates on the two-dimensional code contour line, which can calculate the two-dimensional code...
Through analysis and study of emotional characteristics in Chinese micro-blog, such as Sina Weibo, this paper proposed a multidimensional sentiment classification method based on micro-blog emoticon by dividing micro-blog into 7 types of emotions categories: happiness, fondness, sorrow, anger, fear, detestation and surprise. We used predefined micro-blog emoticon sets to initial screen large-scale...
In this paper, we propose a fast online learning framework for landmark recognition based on single hidden layer feedforward neural networks (SLFNs). Conventional landmark recognition frameworks generally assume that all images are available at hand to train the classifier. However, in real world applications, people may encounter the issue that the classifier built on the existing landmark dataset...
Although a number of sequence database search tools and post-database search algorithms for filtering target PSMs have been developed, the discrepancy among the output PSMs is usually significant, remaining a few disputable PSMs. We employ a SVM-based learning model to search the optimal weight for each target PSM and develop a new score system, C-Ranker, to rank all target PSMs. Compared with PeptideProphet...
In recent 15 years, the biodiversity of Chongming Dongtan national nature reserve has been dramatically reduced by invasive plants, especially by spartina alterniflora. How to obtain and monitor spatio-temporal change of spartina alterniflora has great practical significance in managing and protecting Chongming Dongtan. Therefore, the main purpose of this paper was to build up a method to recognize...
An update algorithm of least squares support vector machine (LSSVM) is proposed to tackle the time-varying characteristics of the real industrial process. The process variations are concluded to two categories, and accordingly the samples adding and samples replacement are proposed to update the initial LSSVM model incrementally. Then the LSSVM model with proposed updating measures is applied in the...
Many cognitive processes are challenging to study due to their scarce occurrence. Here we demonstrate how pattern recognition and brain imaging can enhance the study of such processes by providing fast, sensitive, and non-intrusive detection of these events. This can enable efficient experimental and clinical intervention. We focus on the study of traumatic events producing flashbacks associated with...
The human voice signal carries much information in addition to direct linguistic semantic information. This information can be perceived by computational systems. In this work, we show that early diagnosis of Parkinson's disease is possible solely from the voice signal. This is in contrast to earlier work in which we showed that this can be done using hand-calculated features of the speech (such as...
This work deals with an Intelligent Tutoring System (ITS) for reading comprehension. Such a system could promote reading comprehension skills. An important step towards building a full ITS for reading comprehension is to build an automated ranking system that will assign a hardness level to questions used by the ITS. This is the main concern of this work. For this purpose we, first, had to define...
This paper presents an empirical study on selecting a small amount of useful unlabeled data with which the classification accuracy of semi-supervised learning algorithms can be improved. In particular, a hybrid method of unifying the simply recycled selection method and the incrementally reinforced selection method is considered and empirically evaluated. The experimental results, obtained using well-known...
Traffic signs automatic recognition was researched in this paper. Traffic signs image preprocessing methods was introduced firstly. Secondly, feature extraction algorithm of traffic signs based on SIFT was elaborated, then a fast SIFT algorithm based on PCA dimensionality reduction was presented to extract the characteristics of traffic signs. Finally, the SVM classifier was studied. A large number...
In this paper, we build a convolutional neural network for gender classification based on facial image. And we take experiments with AR face database. The network is built up with an input layer, two convolutional layers, two down-sampling layers and a full-connected layer. In the experiments, we achieve 92% classification accuracy. We also test it with image rotated 15 degree at most, the average...
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.