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In this paper, music genre classification is performed using an approach which converts audio signals into spectrograms and Mel-spectrograms. These spectrograms are treated as texture images from which the following features are extracted: Local Binary Pattern (LBP), uniform Local Binary Pattern (uLBP) and Rotation Invariant LBP (RILBP). The LBP and RILBP features are extracted for having eight equally...
The diagnosis of the arythema disease is a real difficulty in dermatology. It causes redness induced in the lower level of the skin by hyperemia of the capillaries. It can harm several skin damages, inflammations. In this paper, we have put our efforts to design a diagnostic approach based on Support Vector Machine (SVM) with linear kernel by classifying the erythemato-squamous disease. SVM being...
Both M81 and B95-8 are distinct strains belonged to Epstein-Barr Virus (EBV). However, as M81's target cell is epithelial cell and that of B95-8 is B cell, and common EBV vaccine only causes an effect only on B95-8, we can recognize that these two EBVs have different characteristics. In this paper, we analyzed DNA sequence using three algorithms: Apriori, Decision Tree, and support vector machine...
Recent developments in radio technology and processing systems, Wireless Sensor Networks (WSNs) are tremendously being used to perform an assortment of tasks from their atmosphere. Localization plays the most important task in WSNs. Accuracy is the one of the major problems facing localization. In this paper, we propose an improved localization algorithm based on the learning concept of support vector...
The accuracy of photovoltaic (PV) power forecasting decreases drastically under cloudy weather due to the rapid, violent and irregular fluctuation of solar irradiance. Therefore, to improve the accuracy of PV power forecasting, a detailed study on the influence of clouds in different movement and evolution patterns on solar irradiance is very necessary. The classification and recognition of different...
The performance of any machine based recognition system heavily depends on the types of features used. More accurate the features extracted are, better is the chance of getting enhance performance in the recognition system. With this aim in mind a feature extraction method is proposed for numerals of Indian languages. It has been observed that structural feature are having an edge over the statistical...
While systematic reviews (SRs) are positioned as an essential element of modern evidence-based medical practice, the creation and update of these reviews is resource intensive. In this research, we propose to leverage advanced analytics techniques for automatically classifying articles for inclusion and exclusion for systematic review update. Specifically, we used the soft-margin Support Vector Machine...
Recently, a lot of research on the use of big data is made, and this paper was aimed to perform classification experiments using CNN for the detected object collected from traffic detectors. In addition the experimental results were compared with the HOG descriptor that is commonly used in existing pedestrian and object classification and wavelet, texture and descriptor that are used in the road surface...
Different features are extracted for Pattern Recognition using an efficient algorithms like Scale Invariant Feature Transform, Rotation invariant Radon Transform and extracting statistical features of a texture image. Support vector machine with RBF kernel in Weka is used in this paper for classification. This paper shows method to classify the clothing texture patterns like strips, plaid, pattern...
The advancement of medical image digitization and storage is growing day by day and it has resulted in increasing demands for efficient medical image retrieval system. CBIR refers to the retrieval of similar images based on the given query image. Today, Computer Aided Detection/Diagnosis (CAD) schemes that uses CBIR has been attracting research interest. The mammography is the key imagery for early...
In this paper, a method is proposed to predict the putt outcomes of golfers based on their electroencephalogram (EEG) signals recorded before the impact between the putter and the ball. This method can be used into a brain-computer interface system that encourages golfers for putting when their EEG patterns show that they are ready. In the proposed method, multi-channel EEG trials of a golfer are...
The expandable and dynamic web which is a huge repository for information is growing at lightning speed and hence it is hard to find the relevant information from the web. Efficient algorithms reduce the burden of search engines up to a great extent. Query classification is one such aspect and thus a valuable asset for a search engine. Everyday millions of web queries are posted on the web. The main...
Based on principal component analysis (PCA) and support vector machine (SVM), a new method for the fault diagnosis of TE Process is proposed. The fault recognition based on kernel principal component analysis (KPCA) is analyzed and SVM is employed as a classifier for fault classification. To establish a more efficient SVM model, genetic algorithm (GA) is used to determine the optimal kernel parameter...
Aiming at the problem of low accuracy in intrusion detection system, this paper established a genetic support vector machine (SVM) model according to the features of genetic algorithm and support vector machine algorithm. The model firstly optimizes the support vector parameters according to genetic algorithm, then we build the intrusion detection model with support vector machine optimized and use...
Supervised leaning classifier is usually constructing based on models through learning to achieve high accuracy. Support Vector Machine (SVM) is more useful classification technique in supervised learning model. In this paper, we examined SVM with linear kernel function and pre-computed kernel function using micro array data sets. In this observation is focused major three aspects such as accuracy,...
This paper presents an improved vision-based algorithm for detecting and recognizing vehicle logos in images captured by road surveillance cameras. Vehicle logo recognition is quite a challenging task considering the low resolution of the logos, the wide range of variability in illumination and the interference of the air-intake grille. However, our system, assessed on a set of 1386 vehicle images...
In the wireless sensor network (WSN), the operation reliability is usually evaluated by processing measured datas at network nodes. As the traditional algorithms exist the problems of the complex calculation and large energy consumption, a method for fault diagnosis of nodes in WSN based on rough set theory (RS) and support vector machine (SVM) is proposed in this paper. In this paper, we collect...
Human machine interaction is one of the most burgeoning area of research in the field of information technology. To date a majority of research in this field has been conducted using unimodal and multimodal systems with asynchronous data. Because of the above, the improper synchronization, which has become a common problem, due to that, the system complexity increases and the system response time...
Outlier detection is a method to improve performances of machine learning models. In this paper, we use an outlier detection method to improve the performance of our proposed algorithm called decision boundary making (DBM). The primary objective of DBM algorithm is to induce compact and high performance machine learning models. To obtain this model, the DBM reconstructs the performance of support...
Gender classification can play a significant role in security and surveillance system. It aids in identification of a person by recognizing its gender (male/female) from the face image only. Extracting discriminate features for male and female is a fundamental and challenging problem in the field of computer vision. In this manuscript, a combination of Approximation Face Image (AFI) with Principal...
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