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Clustering is a very widely used data mining task practiced to partition data in to similar groups/clusters. Data clustering can be challenging, when it has to be done for huge data sets as no single clustering algorithm proves to give optimal results. Clustering ensembles is an emerging solution to the above issue for improving robustness, stability and accuracy of unsupervised clustering. The clustering...
This paper presents a online multi-font numeral recognition method, whose main aim is to recognize overlaid time numeral from video. The portion of the video frame containing the time text is binarized and segmented. Minimum rectangular bounding box is inserted over the isolated numeral images. Euler number of numeral images is found out to initially differentiate into three groups. Then, the numerals...
Vagueness in the boundaries of land cover classes is one of the important problems in the image classification. Fuzzy c means (FCM) is a traditional clustering algorithm that has been widely used in the satellite image classification. However, this algorithm has the drawback of falling into a local minimum and it needs much time to accomplish the classification for a large data set. In order to overcome...
This paper describes an automated algorithm for plague detection in Intra Vascular Ultrasound images, using an adaptive border detection method for selection Region of Interest (RIO) and detect the soft and hard plague. As shadow appears behind the calcification plaque, it makes it difficult especially for soft plague. Our algorithm divided by two mail part; one, border detection and selection the...
In this paper, we present a novel approach towards combining various machine learners. Our novel approach shows an increase in the accuracy for solving the classification problems in machine learning. We first present a technique of combining learners and also show its implementation using Python programming and then show its comparison with other learners. Later we discuss feature space design and...
Multiplication is a significant process in digital signal processing algorithms. These algorithms involve large number of multiplications, which is time consuming. In digital signal applications time is more important as compared to accuracy. In this paper a simple and efficient architecture of multiplier is proposed which uses adders, shifters, encoders and decoder etc. that consume less area, time...
Many of the distributed environments like internets, intranets, local area networks and wireless networks have different distributed data sources. Inorder to analyze and monitor these distributed data sources specialized data mining technologies for distributed applications are required. A variety of distributed document clustering algorithms exists for this purpose. This paper presents an Enhanced...
Feature selection is a vital process in classification of medical datasets. This paper addresses feature selection in Radial Basis Function (RBF) kernel space for the classification of multiclass dermatology dataset using neural network and data mining classifiers. It has three stages in determining relevant and irrelevant features for the classification task. In stage I, the features of dermatology...
Wireless sensor networks (WSNs) are widely used in many environments and adverse terrains. Location estimation of sensor nodes is still a crucial area of research because of new localization requirements. One of the main hurdles facing sensor localization in WSNs is accuracy. Many localization algorithms and techniques have been proposed to estimate the position of nodes. In this paper, we consider...
The use of the web increases day-by-day. User visits the pages and gives the feedback about the content of the web page. If a user is paying attention on the content of a web page, he spends more time in comparison to the other pages. User chooses some click on the particular page for search query content. These clicks are stored on server log file for measuring the web page importance on the basis...
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...
This paper proposes a text independent method for the classification of normal and pathological voices. If the classifier is text dependent i.e classifier is trained for a particular phoneme, then it may difficult for the patient to pronounce the particular phoneme. To overcome this difficulty, a text independent classification method is proposed, which uses Mel-Frequency Cepstral Coefficients (MFCCs)...
Data mining techniques have been widely used in clinical decision support systems for prediction and diagnosis of various diseases with good accuracy. These techniques have been very effective in designing clinical support systems because of their ability to discover hidden patterns and relationships in medical data. One of the most important applications of such systems is in diagnosis of heart diseases...
Gestures are used in day to day life like nodding and waving without us being aware of them. It has become an important part in the communication among the humans. In the recent years new methods of Human Computer Interaction (HCI) are being developed. Some of them are based on interaction with machines through hand, head, facial expressions, voice, touch and many are still the current topic of research...
Texture analysis finds central role in automatic inspection, medical image analysis, document processing and remote sensing. The result of deviation in illuminant direction affects the texture appearance. The images present in the universe are not uniform because of changes in scale., orientation and lighting conditions. The feature extraction of the non uniform images was done using gray level co-occurrence...
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