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Principal component analysis (PCA) is a commonly used method for feature extraction and dimensionality reduction. This paper proposes PCA based on similarity/correlation criteria instead of covariance to gain low-dimensional features with high performance in text classification. Experimental results have demonstrated the advantages and usefulness of the proposed method in text classification in high-dimensional...
Vocal imitation is widely used in human communication. In this paper, we propose an approach to automatically recognize the concept of a vocal imitation, and then retrieve sounds of this concept. Because different acoustic aspects (e.g., pitch, loudness, timbre) are emphasized in imitating different sounds, a key challenge in vocal imitation recognition is to extract appropriate features. Hand-crafted...
This paper presents a complete study for palm print identification that aims to see how high recognition accuracy can we reach by comparing some results of the previously used line based methods such as Gabor, Canny filters and Modified Finite Radon Transform to represent palm lines and our proposed method that uses basically Radon Transform to describe a person's palm lines. Radon coefficients are...
Text classification is one of the key methods used in text mining. Generally, traditional classification algorithms from machine learning field are used in text classification. These algorithms are primarily designed for structured data. In this paper, we propose a new classifier for textual data, called Supervised Meaning Classifier (SMC). The new SMC classifier uses meaning measure, which is based...
Lending loans to borrowers is considered one of the main profit sources for banks and financial institutions. Thus, careful assessment and evaluation should be taken when deciding to grant credit to potential borrowers. With the rapid growth of credit industry and the massive volume of financial data, developing effective credit scoring models is very crucial. The literature in this area is very dense...
In modern industrial applications driven by Cyber-physical systems (CPS) it is a challenging task to model and optimize processes such as machine analysis and diagnosis. Since the CPS have to act autonomously, a procedure for automated decision making has to be designed. In our work we concentrate on the design of a decision procedure by a fuzzy classifier approach. For our application on decision...
This work focuses on automatic prediction of the writer's biometrics including gender, handedness and age information. The proposed prediction system is based on the use of Histogram of Oriented Gradients (HOG), which aims to extract gradient directions from the handwritten text. The prediction task is achieved using SVM classifier. Experiments performed on IAM and KHATT datasets, reveal promising...
Traditional Support Vector Regression (SVR) Machine acts as approximating a regression function. This paper, however, proposes a novel multi-class classification approach based on the SVR framework, called Support Vector Regression Machine with Consistency (SVRC). The contributions of this paper are: (1) To implement multi-class classification task, were place the margin term with its l1 norm in the...
Thematic information detection is an important application of remote sensing image. Support vector machine (SVM) has been widely used in MODIS remote sensing detection. However, the difficulty of SVM application is how to select the suitable kernel function for remote sensing image. In this paper, the Sangeang Api volcanic ash cloud on May 30, 2014 is taken as an example, and the linear, polynomial,...
We offer an automated way of estimating the author of a song using only its lyrics content. To this end, we introduce a complete text classification framework which takes raw lyrics data as input and report estimated songwriter. The performance of the system is evaluated based on its classification and retrieval ability on a large dataset of Turkish songs, which was collected in this study. The results...
Analog circuits are abundantly used in today's world. Unexpected failures might result in grave repercussions which is why their fault diagnosis is of utmost importance. We put forward an innovative fault classifier technique using Support Vector Machines (SVM) to identify whether the circuit is functioning properly and to identify the fault. We first train the SVM with sample voltages of a simple...
Auroras are beautiful phenomena and attract many people. However, its physical model still remains a subject of dispute because it is caused by the interaction of diverse areas, such as solar wind, magnetosphere, and ionosphere, and it is difficult to simultaneously obtain data in such wide areas. This paper is devoted to forecasting the onset of brightening of auroras followed by poleward expansion,...
Object recognition technology is an important research field of image understanding and computer vision, with its wide range of application, it attracts more and more attention. HMAX was proposed as a simple and biologically feasible model for object recognition, based on how the visual cortex processes information. However, computational cost is the biggest obstacle of this model. This paper aims...
We present a new approach for feature pooling in human action recognition. Instead of partitioning videos at predefined uniform intervals in a spatial-temporal volume as done with spatial pyramid matching, our method adaptively partitions in a pooling attribute space, defined by multiple trajectory-based cues. The pooling attributes include individual spatial and temporal coordinates of a trajectory,...
In this paper, we propose a novel approach for reader-emotion categorization using word embedding learned from neural networks and an SVM classifier. The primary objective of such word embedding methods involves learning continuous distributed vector representations of words through neural networks. It can capture semantic context and syntactic cues, and subsequently be used to infer similarity measures...
Keystroke dynamics authentication is not as widely used compared to other biometric systems. In recent years, keystroke dynamic authentication systems have gained interest because of low cost and integration with existing security systems. Many different methods have been proposed for data collection, feature representation, classification, and performance evaluation. The work presents a detailed...
With the arrival of population aging society, the health care of the elderly becomes more important. The fall detection algorithm is the core of the fall detection alarm system, so it is the key for the research and development of the fall detection system to analyze and select the appropriate algorithm for the detection of falling. It is one of the most important indicators of elder health monitor...
The unprecedented growth of data in web, social media and the attempt to make the cognitive process using computers make Sentiment Analysis a challenging and interesting research problem. Sentiment Analysis mainly deals with the process of analyzing the sentiments or feelings from someone's expression or piece of information, and also in discovering the cognitive behavior of humans. The usage of computers...
The fast growing use of social networking sites among the teens have made them vulnerable to get exposed to bullying. Cyberbullying is the use of computers and mobiles for bullying activities. Comments containing abusive words effect psychology of teens and demoralizes them. In this paper we have devised methods to detect cyberbullying using supervised learning techniques. We present two new hypotheses...
This paper presents hardware constraints analysis of Gabor filtering operation for its hardware implementation in a real time Facial Expression Recognition System (FERS). Gabor filter is the most common feature extractor employed for the realization of such system. Feature extraction using Gabor filter is efficient and has better discrimination capability. In this work, we have employed software-based...
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