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Classification is a well known of the significant tools used to recognize and examine most sharp information in images. Satellite image processing has become popular in these days because of benefits that those are giving. In any remote sensing particularly, the decision-making way mainly rely on the efficiency of the classification process. Image classification was performed generally and the classification...
In Data Mining classification plays prominent role in predicting outcomes. One of the best supervised classification techniques in Data Mining is Naive Bayes Classification. Naive Bayes Classification is good at predicting outcomes and often outperforms other classification techniques. One of the reasons behind the strong performance of Naive Bayes Classification is due to the assumption of conditional...
In this paper we investigate the role of different temporal windows in classification of functional near-infrared spectroscopy (fNIRS) signals corresponding to mental arithmetic and mental counting for development of a brain-computer interface. Signals are acquired from the prefrontal cortex of four healthy subjects during mental arithmetic and mental counting tasks using a continuous-wave fNIRS system,...
Emotion play an important role at several activities in the present world. Human decision making, cognitive process and interaction between human & machine all the activities depends on human emotions. Facial expression, musical activities and several approaches used to find the human emotions. In this paper EEG is used to find the accurate emotion. Emotion classification is the huge task. Classification...
Brain computer interface technology comes at the beginning of the popular study subject for scientist that of excite all of humanity. By means of that technology it is allowed to control electronic devices for paralyzed or partial paralysis humans to make their lives easier. In literature there have been many cursor movement imagery studies based on electroencephalogram (EEG) signals. However, the...
In this study, a graph-based method based on Gaussian Mixture Modeling (GMM) to classify agricultural products is proposed. The effects of different number of components and smoothing constants to the classification accuracies are investigated during the analyses. Tests are performed over two 4-channel Kompsat-2 satellite images which cover approximately 100 km2 of the Karacabey Plain of the city...
Heart disease is the most important reason of morbidity and mortality in the modern society. For that reason, it is important to have a proper diagnosis of heart disease for patients to live to tell the tale. In order to make the diagnosis system as the efficient one, heart diseases should be classified accurately. In the existing technique, the quality of the extracted rules is poor. So as to increase...
We propose a spectral-spatial linear discriminant analysis method (LDA) for dimensionality reduction in hyperspectral image. The proposed method uses a local scatter of the small neighborhood as a regularizer to incorporate into the objective function of the LDA. The intrinsic idea is to design an optimal linear transformation that makes these samples among the neighborhood approximate the local mean...
Intrusion Detection System (IDS) has increasingly become a crucial issue for computer and network systems. Intrusion poses a serious security risk in a network environment. The ever growing new intrusion types pose a serious problem for their detection. The acceptability and usability of Intrusion Detection Systems get seriously affected with the data in network traffic. A large number of false alarms...
A new method for supervised hyperspectral data classification is proposed. In particular, the notion of Stochastic Minimum Spanning Forests (MSFs) is introduced. For a given hyper-spectral image, a pixelwise classification is first performed. From this classification map, M marker maps are generated by randomly selecting pixels and labeling them as markers for the construction of MSFs. The next step...
Support Vector Machines (SVM) have gained increasing attention due to their classification accuracy, robustness and indifference towards the input data type. Thus, they are widely used in the remote sensing community — and especially among researchers working on hyperspectral datasets. However, since their first publication a lot of enhancements and adaptations have been proposed, many of which aim...
Attribute values may be either discrete or continuous. Attribute selection methods for continuous attributes had to be preceded by a discretization method to act properly. The resulted accuracy or correctness has a great dependance on the discretization method. However, this paper proposes an attribute selection and ranking method without introducing such technique. The proposed algorithm depends...
The class imbalance problem usually occurs in real applications. The class imbalance is that the amount of one class may be much less than that of another in training set. Under-sampling is a very popular approach to deal with this problem. Under-sampling approach is very efficient, it only using a subset of the majority class. The drawback of under-sampling is that it throws away many potentially...
Accuracy is a very important criterion for the classifier in the process of classification. In this paper, a unified paradigm for the calculation of accuracy evaluated different classifier, using topological covering-based granular computing, is presented under the given sample space and different ideal classification assumptions. And corresponding examples for the calculation of accuracy in different...
The detection of central apneas using an unobtrusive pressure sensor array installed in the beds of smart homes could allow comfortable diagnosis of sleep disturbances. To improve central apnea detection, two methods of improving the results of apneas classified by a previously developed method are presented: moving average windowing and window elimination. The first improved classifier sensitivity,...
Hierarchical taxonomies are used to organize and retrieve information in many domains, especially those dealing with large and rapidly growing amounts of information. In many of these domains data also tends to be multi-label in nature. In this paper, we consider the problem of automated text classification in these scenarios. We present a post-processing based approach that performs smoothing on...
The method of type functional application is employed attempting to resolve Chinese overlapping ambiguity in the area of Chinese word segmentation. Instead of traditional methods which treat Chinese overlapping ambiguity as classification problems, the proposed approach regards this task as a sentence type calculus problem. The method is based on type theory and the benefit of this method is that...
Recognition of hand gestures associated with different alphabets is a very important research area. The persons with vocal and hearing disabilities may benefit a lot from this research. The communication gap between these and normal persons can be filled by providing an aid in the form of a computerized translation of different hand gestures. In this paper, we have developed a recognition system to...
This paper presents a novel 3D surface texture classification method based on self-similarity maps which are calculated directly from raw captured texture images. 3D surface textures have special properties for they are sensitive to illumination and view conditions. Some previous classification methods which are illumination invariant or rotation invariant have shown to be effective to this particularity,...
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