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The interoperability testing of CTCS-3 Level Train Control System guarantees the safe operation of train running on different lines. It makes great sense to achieve automatic analysis of interoperability testing results, which could improve the efficiency and accuracy of testing. In this paper, a research was conducted on automatic analysis of testing results for on-board equipment of train control...
The aim of this paper is to classify the object in hyper spectral images which are high dimensional images and consists of many data channels. Another aim is to use machine learning classification algorithm like support vector machine (SVM) which is good for high dimensional data case. SVM provides a good accuracy of classification. A statistical model is developed to learn and classify hyper spectral...
This paper aims to experimental evaluation of different methodologies to recognize human face based on different facial expression. The face and facial images were captured locally, as the experiment is aimed to be done in India domain. The features were extracted based on two techniques, viz, Discrete Wavelet Transform (DWT) and Local Binary Pattern (LBP). The range of extracted feature is 150,300,600,1200...
Texture classification is a problem that has variousapplications such as remote sensing and forest speciesrecogni- tion. Solutions tend to be custom fit to the datasetused but fails to generalize. The Convolutional NeuralNetwork (CNN) in combination with Support Vector Machine(SVM) form a robust selection between powerful invariantfeature extractor and accurate classifier. The fusion ofexperts provides...
The Classroom Attentiveness Classification Tool (ClassACT) is a system designed to monitor student attentiveness in a variety of instructional phases within the learning environment: lectures, group work, assessments, etc. By collecting information about the user, the user's environment, and the device itself via the various sensors built in to the tablet, processing the data, and then passing it...
This paper presents a novel technique of image classification using BOVW model. The entire process first involves feature detection of images using FAST, the choice made in order to speed up the process of detection. Then comes the stage of feature extraction for which FREAK, a binary feature descriptor is employed. K-means clustering is then applied in order to make the bag of visual words. Every...
This research is motivated through the demand to create routing in indoor environment based on activity recognition approach. A model to discriminate between walking, climbing up stair, and climbing down stair is introduced. Data was collected from a group of participants performing walking up stairs, walking down stairs, and walking on normal path inside the building. 35 features are considered in...
A Regionlet model explored here provides a new object representation strategy for generic object detection, which integrates local deformation handling into object classifier learning and feature extraction. Generic object detection deals with different degrees of variations in discrete object classes with tractable computations and hence faces problems. This generates a need for representational...
Speech impaired people are detached from the mainstream society due to the lacking of proper communication aid. Sign language is the primary means of communication for them which normal people do not understand. In order to facilitate the conversation conversion of sign language to audio is very necessary. This paper aims at conversion of sign language to speech so that disabled people have their...
Crackles, which are a kind of abnormal lung sounds, are used as indicators for the diagnosis of pulmonary diseases. In this paper, an automatic and noninvasive method is presented for crackles detecting. This method mainly comprises three steps: preprocessing, features extracting and crackles detecting based on support vector machines(SVM). The features are fmin/fmax of the frequency limbic signal,...
We study in this paper an authorship attribution in Arabic poetry using text mining classification. Several features such as Characters, Poetry Sentence length; Word length, Rhyme, Meter and First word in the sentence are used as input data for text mining classification algorithms Naïve Bayes NB, Support Vector Machine SVM, and Sequential Minimal Optimization SMO. The data set of experiment was divided...
Feature extraction addresses the problem of finding the most compact and informative set of features. To maximize the effectiveness of each single feature extraction algorithm and to develop an efficient intrusion detection system, an ensemble of Linear Discriminant Analysis (LDA) and Principle Component Analysis (PCA) feature extraction algorithms is implemented. This ensemble PCA-LDA method has...
Supervised classification techniques use labeled samples in order to train the classifier. In a hyperspectral image, usually the number of such samples is limited, and as the number of bands available increases, this limitation becomes more severe. Such consequences suggest the need for reducing the dimensionality via a preprocessing method. This reduction should enable the estimation of feature extraction...
Support vector machines (SVM), originally introduced as powerful binary classifiers, can also be used for multi-class recognition with the help of creative meta-learning strategies such as commonly used one-vs-rest, one-vs-one and majority voting. In this paper, we explore the potential of creating informed nested dichotomies based on clustering pseudo-labels and probability estimates generated a...
In this paper a new vulnerability detecting method is proposed to detect buffer boundary violations. The main idea is to use the metric of array index manipulation rather than using any heuristic method. We employ a SVM-based classifier to classify the vulnerable functions and innocent functions. Then the vulnerable functions are fed to function call graph guided symbolic execution to precisely determine...
Post stroke rehabilitation exercises are often repetitive and monotonous. Interactive gaming technology plays an important role of encouraging patients to exercise more and makes rehabilitation exercises less monotonous. In this paper, a real-time method for interaction between human and computer is explored which utilizes Microsoft Kinect to measure hand movements and detect grasp gesture. This approach...
Image classification using kernels have very great importance in remote sensing data. The goal of this work is to efficiently classify the large set of aerial images into different classes. This paper introduces a kernel based classification for aerial images. It uses Grand Unified Regularized Least Square (GURLS) and library for support vector machines (LIBSVM). This paper compares the performance...
Playback attack detection (PAD) is essentially a binary classification task which is used to identify the authentic recordings from the playback recordings. For PAD problem, the difference of the acoustic feature between the authentic and playback recordings mainly comes from the recording channel and the ambient noise. Motivated by the excellent performance of the Gaussian Mixture Model-Universal...
Myocardial infarct cause myocardial tissue disease increasing the probability to have arrhythmias such as ventricular fibrillation, these cardiac problems are cause of death. This paper implement a support vector machine classifier trained with the JTp/JT, Tpe/JTp and Tpe/JT intervals ratios extracted from ECG signals of healthy patients and patients with post myocardial infarct diagnosis. The accuracy...
Reciprocating compressors are widely used in the petroleum industry, and a small fault in reciprocating compressors may cause serious issues in operation. Monitoring and detecting potential faults help compressors to continue normal operation. This paper proposes a fault-diagnosis system for compressors using machine-learning techniques to detect potential faults. The system has been evaluated using...
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