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.
Recognition of human actions is an intelligent way for human-machine communication and Radial basis function (RBF) models are among the most powerful machines on this task. One prerequisite of using this traditional model is that the movement data must be translated into a vector space via the feature extraction process. Recent development of the convolutional neural networks (CNNs) has been shown...
The gene structure is consist of intron, exons, promoter, start codon, stop codon, etc. for the eukaryotic organism. The boundary between intron and exon is splice site. There is the need for accurate algorithms to be used in the splice sites identification and more attention was paid during past few years. This proposed system, Splice Hybrid have three layered architecture — in this layer2nd orderMM...
Representation of data is very important in case of machine learning. Better the representation, the classifiers will give better results. Contractive autoencoders are used to learn the representation of data which are robust to small changes in the input. This paper uses contractive autoencoder and SVM classifier for handwritten Devanagari numerals recognition. The accuracy obtained using CAE+SVM...
Development of smart cities has grasped much attention in research community and industry as well. Smart healthcare, communication, infrastructure are required for the development of smart cities. Security is one of the major concern in the development of smart cities. Automatic surveillance helps in boosting security in multiple areas like traffic, hospitals, schools, and industries etc. Video camera...
This work seeks to improve upon the accuracy of birdsong analysis based species recognition. We intend to accomplish this by creating a more effective bird syllable segmentation algorithms (MIRS), Support Vector machine based classifiers are used to train the features of IRS and MIRS. The experimental results show the effectiveness of the proposed algorithm.
In this article we applied Support Vector Machines to acoustic model of Speech Recognition System based on MFCC and LPC features for Azerbaijani DataSet. This DataSet has been used for speech recognition by Multilayer Artificial Neural Network and achieved some results. The main goal of this work is applying SVM techniques to the Azerbaijan Speech Recognition System. The variety of results of SVM...
Fraud is a threat that most online service providers must address in the development of their systems to ensure an efficient security policy and the integrity of their revenue. If rule-based systems and supervised methods usually provide the best detection and prevention, labelled training datasets are often non-existent and such solutions lack reactivity when facing adaptive fraudsters. Many generic...
Human gesture recognition has been an active and challenging problem, especially when motion capture devices become more popular. Various studies have shown that support vector machines (SVMs) with Gaussian kernels are among the most prominent models for an accurate gesture classification. We demonstrate in this paper that the relevance vector machines (RVMs) could also achieve the state-of-the-art...
We present a novel approach to automated estimation of agreement intensity levels from facial images. To this end, we employ the MAHNOB Mimicry database of subjects recorded during dyadic interactions, where the facial images are annotated in terms of agreement intensity levels using the Likert scale (strong disagreement, disagreement, neutral, agreement and strong agreement). Dynamic modelling of...
With the development of the Internet, people share their emotion statuses or attitudes on online social websites, leading to an explosive rise on the scale of data. Mining sentiment information behind these data helps people know about public opinions and social trends. In this paper a sentiment analysis algorithm adapting to Weibo (Microblog) data is proposed. Given that a Weibo post is usually short,...
Automatic facial action unit (AU) detection is a challenging research topic in computer vision and pattern recognition. Most of the existing approaches design classifiers to detect AUs individually without considering their intrinsic relations. This paper proposes a novel framework to jointly learn the classifiers for detecting the presence and absence of multiple AUs. In our method, hierarchical...
In this work, we propose a method to identify the ragas of an Indian Carnatic music signal. This has several interesting applications in digital music indexing, recommendation and retrieval. However, this problem is hard due to (i) the absence of a fixed frequency for a note (ii) relative scale of notes (iii) oscillations around a note, and (iv) improvisations. In this work, we attempt the raga classification...
Support vector machines (SVM) were originally developed for binary classification and extended for multi-class classification. Due to their powerfulness and adaptation to hard classification problems, we have chosen them for automatic speech recognition (ASR). The aim of this paper is to investigate the use of SVM multi-class classification coupled with HMM for TIMIT phones. SVM requires that all...
Classifiers in Automatic Speech Recognition (ASR) aims to improve the generalization ability of the machine learning and improve the recognition accuracy in noisy environments. This paper discusses the classification performance of Hidden Markov Models (HMM) and Support Vector Machines (SVM) applied to a wavelet front end based ASR. The experiments are performed on speaker independent TIMIT database...
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...
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...
Most approaches to learn classifiers for structured objects (e.g., images) use generative models in a classical Bayesian framework. However, state-of-the-art classifiers for vectorial data (e.g., support vector machines) are learned discriminatively. A generative embedding is a mapping from the object space into a fixed dimensional score space, induced by a generative model, usually learned from data...
We propose a landmine detection algorithm using ground penetrating radar data that is based on an SVM classifier. The kernel function for the SVM is constructed using discrete hidden Markov modeling (HMM). Typically, the kernel matrix could be obtained by defining an adequate similarity measure in the feature space. However, this approach is inappropriate as it is not trivial to define a meaningful...
The study of the behavior of ion-channels can provide significant information to detect metal ions and small organic molecules in solution. Discrimination of different analytes can be performed by extracting appropriate features from the ion-channel signals and using them for classification. In this paper, we consider features extracted from the Fourier, Wavelet and Walsh-Hadamard domain representations...
Information on the vehicular traffic density in an intelligent transport system (ITS) is presently obtained mainly through loop detectors (LD), traffic radars and surveillance cameras. However, the difficulties and cost of installing loop detectors and traffic radars tend to be significant. Currently, a more advanced method of circumventing this is to develop a sort of virtual loop detector (VLD)...
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.