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.
An intelligent classification technique for MR brain images are extremely important for medical analysis and treatment selection. Manual interpretation of these images by physicians may lead to wrong diagnosis when a large number of MRIs are analyzed. In this paper an automated decision support system for classification is proposed. It consists of computing the uniform LBP with mapping. Haar wavelet...
Prognostic of future health state relies on the estimation of the Remaining Useful Life (RUL) of physical systems or components based on their current health state. RUL estimation can be done by using three main approaches: model-based, experience-based and data-driven approaches. This paper deals with a data-driven prognostics method which is based on the transformation of the data provided by the...
Network Intrusion Detection System (NIDS) plays an important role in providing network security. Efficient NIDS can be developed by defining a proper rule set for classifying network audit data into normal or attack patterns. Generally, each dataset is characterized by a large set of features, but not all features will be relevant or fully contribute identifying an attack. Since different attacks...
In this paper, we propose a protein secondary structure prediction method based on the support vector machine (SVM) with position-specific scoring matrix (PSSM) profiles and four physicochemical features, including conformation parameters, net charges, hydrophobic, and side chain mass. First, the SVM with the optimal window size and the optimal parameters of the kernel function is found. Then, we...
Automatic adult video detection is a problem of interest to many organizations around the world. The aim is to restrict the easy access of underage youngsters to such potentially harmful material. Most of the existing techniques are mere extensions of image categorization approaches. In this paper we propose a video genre classification technique tuned specifically for adult content detection by considering...
Classification accuracy is one of major factors influencing the application of classified image. This Paper proposes a SVM-based multiple classifiers fusion method for remote sensing image classification. We use both spatial Gabor wavelet texture feature and spectral feature to construct SVM classifier separately. then taking advantage of characteristic of SVM, namely for a given sample, the larger...
This paper introduces a classification system for remote sensing ASTER satellite imagery using SVM and particle swarm optimization (PSO) algorithm. The proposed system starts with the identification of selected area of study. This is followed by a pre-processing phase using mapping polynomial algorithm as geometric correction. Followed by, applying threshold algorithm for image segmentation. Then...
A new gearbox fault prognosis scheme based on continuous hidden Markov model (CHMM) and support vector machine (SVM) is developed. Based on the features which are the energies of intrinsic mode functions (IMFs) decomposed by empirical mode decomposition (EMD) extracted from normal gearbox vibration signal, a CHMM is trained to model the normal condition. The logarithm of the probability of this CHMM...
In this work the authors propose a classification method based on Support Vector Machine (SVM) and key frames features extraction to classify historical sport video contents. In the context of the Italian Project, IRMA (Information Retrieval in Multimedia Archives), with the goal to recover and preserve historical videos of proven cultural interest, a data set made up of several hours of videos from...
Obstructive sleep apnea (OSA) is a common disorder in which individuals stop breathing during their sleep. Most of sleep apnea cases are currently undiagnosed because of expenses and practicality limitations of overnight polysomnography (PSG) at sleep labs, where an expert human observer is needed to work over night. New techniques for sleep apnea classification are being developed by bioengineers...
In this paper, we propose a hybrid generative discriminative framework for the challenging problem of spam emails filtering using both textual and visual features. Our framework is based on building probabilistic Support Vector Machines (SVMs) kernels from mixture of Langevin distributions. Through empirical experiments, we demonstrate the effectiveness and the merits of the proposed learning framework.
Font can be used as a notion of similarity amongst multiple documents written in same script. We could automatically retrieve document images with specific font from a huge digital document repository. So Optical Font Recognition could be a useful pre-processing step in an automated questioned document analysis system for sorting documents with similar fonts. We propose a scheme to identify 10 different...
With increasing amounts of data being generated by businesses and researchers, there is a need for fast, accurate and robust algorithms for data analysis. Improvements in database's technology, computing performance and artificial intelligence have contributed to the development of intelligent data analysis. The primary aim of data mining is knowledge discovery, i.e. patterns in the data that lead...
In this paper a new identification technique for buried landmine objects is presented. Most of the existing supervised identification methods are based on traditional statistics, which can provide ideal results when sample size is tending to infinity. However, only finite samples can be acquired in practice. In this paper, a proposed learning method, Support Vector Machine (SVM), is applied on landmine...
The growing productions of maps are generating huge volumes of data that exceed people's capacity to analyze them moreover these data sets have different resources and types. It seems appropriate to apply knowledge discovery methods like data mining to spatial data so, one of the most significant application in spatial data mining is classification for remote sensing images. This paper proposes a...
Automatic image annotation is the process by which a computer system automatically assigns metadata in the form of captioning or keywords to a digital image. This application of computer vision technique is used in image retrieval system to organize and locate images of interest from a database. Many techniques have been proposed for image annotation in the last decade that gives reasonable performance...
Protein-Protein Interaction (PPI) extraction from biomedicine literature can supply the biomedicine researcher with useful information rapidly. This paper presents a PPI extraction system based on the ensemble kernel model and active learning. Firstly, the ensemble kernel within SVM classifier combines the lexical feature-based kernel and the path-based kernel. Experimental results show that the F-score...
This work describes a Support Vector Machine (SVM) method used to analyze ECG signals for diagnosing cardiac arrhythmias effectively. The proposed method can accurately classify and differentiate normal (Normal) and abnormal heartbeats. Abnormal heartbeats include left bundle branch block (LBBB), right bundle branch block (RBBB), atrial premature contractions (APC) and premature ventricular contractions...
Feature fusion method has improved steganographic detection performance based on classical feature, however there are some drawbacks of this: without analysing the correlation of the basic features, it's only a simple combination of features and lacks standard for features selection; serial fusion feature always has high dimension, which will lead great time cost and possibility of “curse of dimensionality”...
In the Brain-computer interface, classification and recognition technology plays an important role, especially the EEG classification and recognition for the movement imagery. In this paper, we use a new type of sensors to collect EEG signals. According to imagine the movement of left or right hand to identify two types of thinking, we proposed a new recognition method based on AR(auto-regressive)...
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.