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.
Paper proposes a novel experimental environment for solving a classic nonlinear Soft Margin L1 Support Vector Machine (SVM) problem using a Stochastic Gradient Descent (SGD) algorithm. Our implementation has a unique method of random sampling and alpha calculations. The developed code produces a competitive accuracy as well as very fast training of SVMs (small CPU time). The SGD model's performance...
In most document archiving systems, one of the main fields is to identify the category of documents. In most case, determination of the document category in archiving tasks requires the application of classification model, which have had successes in improving documents processing. However, concerns exploding the frequency of use of documents in many office managers have driven increasing interests...
Epigenetics is the study of heritable changesin gene expression that does not involve changes to theunderlying DNA sequence, i.e. a change in phenotype notinvolved by a change in genotype. At least three mainfactor seems responsible for epigenetic change including DNAmethylation, histone modification and non-coding RNA, eachone sharing having the same property to affect the dynamicof the chromatin...
Paying attention to different pictures is related to complex information processing in the brain. Categorizing visual objects using the electroencephalogram (EEG) signal of subject along with paying attention to pictures, is properly possible. The aim of this paper is to analyze the mental signal in order to show the differences in cognitive patterns during paying attention to sets of different pictures...
Real-time strategy games are strategic war games where two or more players operate on a virtual battlefield, controlling resources, buildings, units and technologies to achieve victory by destroying others. Achieving victory depends on selecting a suitable plan (set of actions), selecting a suitable plan depends on building an imagination (building a model) of the opponent to know how to deal with...
Hyperspectral imaging is the procedure to gather and handle information across the electromagnetic spectrum. The fundamental objective of hyperspectral imaging is to achieve the spectrum for every pixel in the picture. The spectrum helps in computer vision, i.e., locating items, material detection or process discovery. This approach is constantly developing in the field of remote sensing applications...
Many researchers have used the Heat Kernel Signature (or HKS) for characterizing points on non-rigid three-dimensional shapes and Classical Multidimensional Scaling (Classical MDS) method in object classification which we quote, in particular, the example of Jian Sun et al. (2009) [1]. However, in this paper, the main focuses on classification that we propose a concise and provably factorial method...
Big Data Analytics methods take advantage of techniques from the fields of data mining, machine learning, or statistics with a focus on analysing large quantities of data (aka ‘big datasets’) with modern technologies. Big data sets appear in remote sensing in the sense of large volumes, but also in the sense of an ever increasing amount of spectral bands (i.e., high-dimensional data). The remote sensing...
The reliability of support vector machines for classifying multi-spectral images of remote sensing has been proven in various studies. In this paper, we investigate their applicability for urban land cover in Wuhan, Hubei province of China. Firstly, radiation rectification, normalization processing and geometry registration are made between the bi-temporal images. Secondly, SVM approach is used in...
Multiple kernel learning (MKL) combines multiple base kernels and is becoming more and more popular in machine learning. The choice of kernels is crucial importance for classification performance. In this paper, we propose a new RMKL (RMKBoost) framework for classification in hyperspectral images. The classification is performed in separate two steps. The key boosting strategy is embedded in the first...
Chronic kidney disease is a universal common obstacle which its outcomes can be prevented or delayed by early detection and cure. Classification of kidney disease is vital for global improvement and accomplishment of practical guidance. Therefore, data mining and machine learning techniques can be used to discover knowledge and identify patterns for classification. Since there exist features that...
With the computational power available today, machine learning is becoming a very active field finding its applications in our everyday life. One of its biggest challenge is the classification task involving data representation (the preprocessing part in a machine learning algorithm). In fact, classification of linearly separable data can be easily done. The aim of the preprocessing part is to obtain...
In this paper, classifying and indexing hierarchical video genres using Support Vector Machines (SVMs) are based on only audio features. In fact, segmentation parameters are extracted at block levels, which have a major benefit by capturing local temporal information. The main contribution of our study is to present a powerful combination between the two employed audio descriptors; Mel Frequency Cepstral...
Reducing unnecessary lab tests is an essential issue in intensive care unit (ICU). In this paper we analyze lab tests ordered for ICU patients using data mining methods. The selected dataset is extracted from Multi-parameter Intelligent Monitoring in Intensive Care II (MIMIC-II) database. Calcium test is selected as the target test which is one of the frequent tests for gastrointestinal bleeding patients...
Accurate detection of life-threatening cardiac ailments is one of the important task in monitoring patient's health. In this paper, a new method for detection and classification of cardiac ailments from multilead electrocardiogram (MECG) is presented. The singular value decomposition (SVD) is used to convert the MECG data matrix into two unitary matrices (eigen matrices) and one diagonal matrix. According...
This paper presents a novel multikernel based Sparse representation for the classification of Remotely sensed images. The sparse representation based feature extraction are in a run which is a signal dependent feature extraction and thus more accurate. Multikernel Sparse representation was also had proved to be more accurate and less computationally complex while implemented in other applications...
Jamu is an Indonesia herbal medicine made from natural materials such as roots, leaves, fruits, and animals. The purpose of this research is to develop a classification system for jamu efficacy based on the composition of plants using Support Vector Machine (SVM) and to implement the k-means clustering algorithm as a feature selection method. The result of this study was compared to the previous research...
In this paper, we present VLSI architecture of Pairwise Linear Support Vector Machine (SVM) classifier for multi-classification on FPGA. The objective of this work is to facilitate real time classification of the facial expressions into three categories: neutral, happy and pain, which could be used in a typical patient monitoring system. Thus, the challenge here is to achieve good performance without...
This paper presents a novel histogram based attribute profiles (HAPs) technique for classification of very high resolution remote sensing images. The HAPs characterize the marginal local distribution of attribute filter responses to model the texture information. This is achieved based on a two steps algorithm. In the first step the standard attribute profiles (AP) are built through sequential application...
In this paper, two contributions are made. Firstly, we propose a discriminating multiple kernel learning (DMKL) algorithm to solve the combination coefficient of basic kernels by maximizing the separability in the kernel Hilbert space in the process of MKL. The core idea of the proposed algorithm is to find the optimal projective direction, which projects the basic kernels to a discriminating kernel,...
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.