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Parameters selection of support vector machine (SVM) is a key problem in the application of SVM, which has influence on generalization performance of SVM. The commonly used method, grid search (GS), is time-consuming especially for very large dataset. By using coarse grid search and pattern search (PS) to select kernel parameters and penalty factor, a fast method of parameters selection of SVM based...
Classification of structural magnetic resonance imaging (sMRI) brain scans is helpful to detect Alzheimer's disease (AD) at its early stage. In this paper we present a classification scheme that combines the uncorrelated multilinear principal component analysis (UMPCA) and Laplacian Score (LS) methods, which are known to be effective to the structural correlation preserving and redundancy reduction...
We introduce a new method for representing the dynamics of human-object interactions in videos. Previous algorithms tend to focus on modeling the spatial relationships between objects and actors, but ignore the evolving nature of this relationship through time. Our algorithm captures the dynamic nature of human-object interactions by modeling how these patterns evolve with respect to time. Our experiments...
Since emotion technology has been applied into numerous applications, the role of recognizing human emotion has become more important. In this paper, two autonomic nervous signals such as SKT and PPG were analyzed in order to extract 2D emotional feature vector (PPI and SKT amplitude) for classification between happy and sad emotions. A support vector machine was adopted for non-linear classification...
Image processing is having very important role in medical domain. Melanoma skin cancer is critical and dangerous for human beings. Early detection of Melanoma skin cancer is very much necessary for the patient because this Melanoma skin cancer directly lead to the death of a person. If it is detected at early stage then Melanoma skin cancer is completely curable. In this paper early detection and...
Since the inception of the concept of social networking, communication patterns have shifted drastically with the unmitigated trend in socializing over the Internet, especially when people began connecting via mobile devices. Nowadays people tend to use these modern communication systems to share their emotions with each other. Human emotions play a vital role in human relationships and people share...
The basic goal of this work is to develop a Consonant-Vowel Recognition System (CVRS) for determining a sequence of Consonant-Vowel (CV) units present in a given speech utterance. In this work, we are focusing on developing CVRSs for Indian languages namely Bengali and Odia. This framework of developing CVRSs can be extended to any Indian languages. We have developed two separate CVRSs for Bengali...
Digital visual media is one of the most commonly used means of communication. But, with the use of low-cost editing tools, tampering and counterfeiting visual contents are increasing enormously. In almost all the Image forensic application areas, the device used for capturing the image is of utmost importance as the origin of the particular image can act as a key evidence to substantiate the legitimacy...
Learning algorithms of the support vector machine is to map the input vector to a high dimensional space through certain kernel function and separate the image of the original linear input vector with the maximum of interval under consideration. This paper is about the limb motion recognition problem of stroke patients, mapping the input vector to the reproducing kernel RKHS (reproducing Kernel Hilbert...
Demand for automatic classification of Brain MRI (Magnetic Resonance Imaging) in the field of Diagnostic Medicine is rising. Feature Selection of Brain MRI is critical and it has a great influence on the classification outcomes, however selecting optimal Brain MRI features is difficult. Particle Swarm Optimization (PSO) is an evolutionary meta-heuristic approach that has shown great potential in solving...
As a widely used medium platform, Micro-blog influence research is a hotspot. The community micro-blog, which is used as an effective tool by social managers in virtual community, has developed rapidly in recent years. As the basis of government micro-blog system in China, the community blog influence has great importance to guide the public popular feelings and guarantee the safety of the virtual...
In this paper, we developed the system for recognizing the orchid species by using the images of flower. We used MSRM (Maximal Similarity based on Region Merging) method for segmenting the flower object from the background and extracting the shape feature such as the distance from the edge to the centroid point of the flower, aspect ratio, roundness, moment invariant, fractal dimension and also extract...
In conventional text categorization algorithms, documents are symbolized as “bag of words” (BOW) with the fact that documents are supposed to be independent from each other. While this approach simplifies the models, it ignores the semantic information between terms of each document. In this study, we develop a novel method to measure semantic similarity based on higher-order dependencies between...
Facial expressions are important in human computer interaction, because the machine can thereby understand human reactions and act accordingly. Facial expressions act like a nonverbal communication cues in human-human or human computer interactions. In noises environment, getting visual data is difficult. According to the relative bin sub-image based studies, high dimensionality is affecting the system...
In order to overcome the shortcomings in traditional anomaly intrusion detection methods, such as low detection rate and high false alarm rate, this paper proposes an intrusion detection method based on wavelet kernel Least Square Support Vector Machine (LS-SVM). As a new machine learning method, SVM has been used in Intrusion Detection System (IDS) recently and achieved certain effects. While the...
Network performance metrics such as available bandwidth and latency are essential to achieve good Quality of Service (QoS) in multimedia streaming. There are unique requirements in network performance metrics for media applications, such as audio conferencing, video streaming, video conferencing, and high-definition (HD) video conferencing. In this paper, we focus on conference call type suggestion...
In this paper, we propose a novel method of anomaly detection in wireless sensor networks (WSN) based on S Transform. It makes use of S transform for feature extraction. We extract only the significant components of the time-series data. Earlier wavelets based approach that extracts features from the time-series data has been applied for detecting anomalies in combination with various classifiers...
This study proposes a clustering-based Wi-Fi fingerprinting localization algorithm. The proposed algorithm first presents a novel support vector machine based clustering approach, namely SVM-C, which uses the margin between two canonical hyperplanes for classification instead of using the Euclidean distance between two centroids of reference locations. After creating the clusters of fingerprints by...
The Local Binary Patterns (LBP) feature extraction method is a theoretically and computationally simple and efficient methodology for texture analysis. The LBP operator is used in many applications such as facial expression recognition and face recognition. The original LBP is based on hard thresholding the neighborhood of each pixel, which makes texture representation sensitive to noise. In addition,...
Jamu is made from natural materials such as roots, leaves, timber and fruits. Jamu has many variations of formula. The composition of Jamu formula is usually based on empirical data or personal experiences. Thus, the classification for the efficacy of Jamu based on its compositions of plants still remains an interesting task. The purpose of this research is to develop a classification system for Jamu...
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