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Fingerprinting Localization Solutions (FPSs) enjoy huge popularity due to their good performance and minimal environment information requirement. Considered as a data-driven approach, many modern data analytics can be used to improve its performance. In this paper, we propose tow learning algorithms, namely a deep learning architecture for regression and Support Vector Machine (SVM) for classification,...
Recently, the combination of classification systems with semi-supervised learning has attracted researchers in several fields. Usually, for tasks with high complexity such as handwriting based age prediction, individual systems, using one classifier associated with specific data features, cannot provide satisfactory performance. In this paper, we investigate the contribution of the Co-training approach,...
This paper evaluates a mechanism for applying machine learning (ML) to identify over-constrained IaaS virtual machines (VMs). Herein, over-constrained VMs are defined as those who are not given sufficient system resources to meet their workload specific objective functions. To validate our approach, a variety of workload-specific benchmarks inspired by common Infrastructure-as-a-Service (IaaS) cloud...
Neuroscience researchers have a keen interest in finding the connection between various brain regions of an organism. Researchers all across the globe are finding new connections everyday and it is very difficult to keep track of all those, so it is important to create a centralized system which is able to give the relation between brain entities. Databases like PubMed contains abstracts and references...
In the field of civil engineering, Ground Penetrating Radar (GPR) is the most widely used method of Non-Destructive Testing (NDT). Using supervised learning methods or signal processing methods, it is possible to analyze the sub-surface defects in pavement. In this paper, we propose to use a supervised machine learning method called Support Vector Machines (SVM) to detect the presence of debondings...
Ground Penetrating Radar (GPR) has been a precious tool for humanitarian demining. The GPR scans the ground and delivers a three-dimensional matrix representing three types of data: Ascan, Bscan and Cscan. The Ascan data represents the response from a reflection signal of a pulse emitted by the GPR at a given position. In the proposed landmine detection method, the Ascan data is normalized and then...
It is well recognized that the signal processing methods contributes in biology to the control of the DNA spatial structure. From the previous studies, it is inferred that the significant portion of the eukaryotic genomes is composed of transposable elements (TEs). The TEs play an important role as a driving force of genome evolution. An important sub class of ETs class II, Helitrons, have been revealed...
Local binary pattern (LBP) has limitation in extracting the edge and direction information, which is vital to infrared face recognition. A new infrared face recognition algorithm fusion of LBP and histogram of oriented gradients (HOG) is proposed. First, LBP operator is adopted to extract the texture feature of an infrared face, and then the edge features of the original infrared face are extracted...
Parkinson's disease (PD) is a neurological disorder associated with a progressive decline in motor skills, speech, and cognitive processes. Since the diagnosis of Parkinson's disease is difficult, researchers have worked to develop a support tool based on algorithms to separate healthy controls from PD patients. Online handwriting analysis is one of the methods that can be used to diagnose PD. The...
We address the problem of automatically recognizing artistic movement in digitized paintings. We make the following contributions: Firstly, we introduce a large digitized painting database that contains refined annotations of artistic movement. Secondly, we propose a new system for the automatic categorization that resorts to image descriptions by color structure and novel topographical features as...
In this paper, we present landmine detection and discrimination method: one class support vector machine (OSVM) based on RBF kernel using one-dimensional Ground Penetrating Radar (GPR) delivered data. The GPR has been a precious tool for humanitarian demining. It scans the ground and delivers a three-dimensional matrix representing three types of data; Ascan, Bscan and Cscan. The Ascan data represents...
Helitron is considered as very important type of DNA involved in mechanism's evolution. These elements are not well studied and the major researches done are biological experiments. In this paper, we propose a novel approach aiming to characterize and classify helitron's types. Accordingly, we use the Support Vector Machine (SVM) classification technique known to be preferment in DNA related studies...
Early diagnosis of stroke is essential for timely prevention and treatment. Investigation shows that measures extracted from various risk parameters carry valuable information for the prediction of stroke. This research work investigates the various physiological parameters that are used as risk factors for the prediction of stroke. Data was collected from International Stroke Trial database and was...
This paper proposes a speech/music classification system based on i-vector. An analysis of two classification methods, namely cosine distance score (CDS) and support vector machine (SVM) is performed. Two session compensation methods, within-class covariance normalization (WCCN) and linear discriminant analysis (LDA) are also discussed. The performance of proposed systems yields better results compared...
We consider the problem of ligand affinity prediction as a regression task, typically with few labelled examples, many unlabelled instances, and multiple views on the data. In chemoinformatics, the prediction of binding affinities for protein ligands is an important but also challenging task. As protein-ligand bonds trigger biochemical reactions, their characterisation is a crucial step in the process...
Recently deep Convolutional Neural Networks have been successfully applied in many computer vision tasks and achieved promising results. So some works have introduced the deep learning into face anti-spoofing. However, most approaches just use the final fully-connected layer to distinguish the real and fake faces. Inspired by the idea of each convolutional kernel can be regarded as a part filter,...
In this paper, the proposed implementation of a soft-biometric system for automatic age detection from facial images is described. In order to do this, the method followed was that of a classical biometric system. The first step is preprocessing, to enhance the feature extraction. The next step is the parameterization, where techniques like wavelet transformed, discrete cosine transformed or local...
Ground Penetrating Radar (GPR) is used for subsurface exploration across different applications like landmines detection. It can detect and deliver the response of any buried kinds of object, however it cannot discriminate between landmines and false alarms. In this paper, we propose a detection method based on support vector machine (SVM) using one-dimensional GPR delivered data called Ascans. Each...
This paper addresses the problem of automatic target recognition (ATR) using inverse synthetic aperture radar (ISAR) images. In this context, we propose a novel approach for feature extraction to describe precisely an aircraft target from ISAR images. In our approach, a visual attention model is adopted to separate the salient regions from the background. After that, the scale invariant feature transform...
This paper proposes a new Utterance Verification (UV) algorithm based on i-vector. Phone segments are extracted and concatenated from the training data, which are used to train the Universal Background Model (UBM) and the Total Variability (TV) matrix, and then, i-vector is extracted from the enrollment and evaluation data using UBM and TV matrix. We compare two Confidence Measures (CMs), cosine distance...
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