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This paper describes basic categories of evaluation tasks, which can be used in area of computer science education process. The goals and weaknesses of automatic testing process by using computer based on automatic evaluation rules are discussed here. Article describes basic areas for testing in education, divides tasks into groups with same semantic and structure. Important part is oriented to describe...
This article presents a clustering-based approach to fuzzy system identification. In order to construct an effective initial fuzzy model, this article tries to present a modular method to identify fuzzy systems based on a hybrid clustering-based technique. Moreover, the determination of the proper number of clusters and the appropriate location of clusters are one of primary considerations on constructing...
Sufficient test coverage for Software Agents that operate in an open and dynamic environment is unlikely to be achieved during the agents' development. Especially when agents exhibit self properties and are constantly adapting to changes in their environment it is important to limit their autonomy to ensure that their behaviour lies within safe boundaries. To increase the trust in the agents, once...
Inspite of the huge amounts of image data on the web, mining image data from the web is paid less attention than mining text data, since treating the semantics of images is much more difficult. This paper introduces a new system to mine visual knowledge on the web that aims to build a Domain Oriented Image Directory by using the Earth Mover's Distance and Color signatures. Instead of using a flat...
This paper discusses the application of two unsupervised methods in classifying type of soils. Soils that are suitable for agricultural activities can be classified into four classes which are hill soil, organic soil, alteration soil and alluvium soil. In addition, no specific support system is able to classify the type of soil and retrieve the information for location and suitable plants for local...
It is well known that the problem arising from high dimensionality of data should be considered in pattern recognition field. Face recognition databases are usually high dimensionality, especially when limited training samples are available for each subject. Traditional techniques perform dimensionality reduction are unable to solve this problem smoothly, which makes feature extraction task much difficult...
Recent library digitization projects attempt to provide large collections of printed material from varying sources in a searchable format. The scanned documents are typically processed using Optical Character Recognition (OCR), which typically introduces errors in the text. This paper proposes a technique for correction of OCR degraded text that is independent of character-level OCR errors, and hence...
Intrusion Detection System (IDS) is an important and necessary component in ensuring network security and protecting network resources and infrastructures. In this paper, we effectively introduced intrusion detection system by using Principal Component Analysis (PCA) with Support Vector Machines (SVMs) as an approach to select the optimum feature subset. We verify the effectiveness and the feasibility...
In classifier combining, predictions of several classifiers are aggregated into a single prediction in order to improve the classification quality. Among others, fuzzy integrals are commonly used as aggregation operators. Usually, Sugeno lambda-measure is used as the fuzzy measure of the integral. However, interaction between the classifiers in the team (diversity), an important property in classifier...
In this paper, we describe an alternative method of the recognition of human irises with the usage of Non-Negative Matrix Factorization. The proposed method has been implemented on graphic processor unit (GPU) which makes the method usable in the real world due to short computation time.
Support Vector Machine (SVM) is one of the most popular tools for solving general classification and regression problems because of its high predicting accuracy. However, the training phase of nonlinear kernel based SVM algorithm is a computationally expensive task, especially for large datasets. In this paper, we propose an intelligent system to solve large classification problems based on parallel...
The problem of object detection in image and video has been treated by a large number of researchers. Many design factors degrade the reliability of the problem solutions, such as manual modeling of the object, manual features selection, handcrafting architecture, and learning algorithm selection. Here, a generalized object detection and localization system is presented. It has the ability to learn...
This paper presents a model of a supervised machine learning approach for classification of a dataset. The model extracts a set of patterns common in a single class from the training dataset according to the rules of the pattern-based subspace clustering technique. These extracted patterns are used to classify the objects of that class in the testing dataset. The user-defined threshold dependence...
In BCI research community, support vector machine (SVM) is an effective method for motor imagery (MI)-based electroencephalographic (EEG) classification. However, the computation of decision function during SVM classification stage for a new EEG trial is time-consuming due to the large number of support vectors (SV). This paper proposes a new method to reduce the number of support vectors so that...
In order to improve the classifier performance in semantic image annotation, we propose a novel method which adopts learning vector quantization (LVQ) technique to optimize low level feature data extracted from given image. Some representative vectors are selected with LVQ to train support vector machine (SVM) classifier instead of using all feature data. Performance is compared between the methods...
Pattern recognition is very challenging multidisciplinary research area attracting researchers and practitioners. Gesture recognition is a specialized pattern recognition task with the goal of interpreting human gestures via mathematical models. One of the usages of gesture recognition is the sign language recognition which is the basic communication method between deaf people. Since there is lack...
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