Kiruparan Balachandran

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Image Segmentations play a heavy role in areas such as computer vision and image processing due to its broad usage and immense applications. Because of the large importance of image segmentation a number of algorithms have been proposed and different approaches have been adopted. In this theme I tried to parallelize the image segmentation using a region(More)
The web mining is a cutting edge technology, which includes information gathering and classification of information over web. This paper puts forth the concepts of document pre-processing, which is achieved by extraction of keywords from the documents fetched from the web, processing it and generating a term-document matrix, TF-IDF and the different(More)
Lung cancer is, one of the groups of malignant diseases affecting the Lung and associated organs. Pre-diagnosis is an important stage of identifying the target group of persons who can undergo diagnosis stage. In this study, a model is proposed based on ensemble of classifiers for prediction of lung cancer based on symptoms and risk factors. Data mining(More)
Artificial Intelligence plays a vital role in developing machines or software that can create intelligence. Artificial Neural Networks is a field of neuroscience which contributes tremendous developments in Artificial Intelligence. This paper focuses on the study of performance of various training algorithms of Multilayer Perceptrons in Diabetes Prediction.(More)
Mathematical Optimization refers to finding the minimum or maximum value from a desired set of outcomes. This paper discusses about optimization in two levels. LevenbergMarquardt is used for back propagation to minimize non-linear least square error using curve fitting. This minimization involves functional optimization to reduce error in neural network(More)
Lung cancer disease is one of the dreaded diseases in the developing and developed countries. The pre-diagnosis is an important stage of identifying the target group of persons who can undergo diagnosis stage. Here in this study, prediction of lung cancer is attempted based on symptoms and risk factors. Data collected from the confirmed case of the patients(More)
Dimensionality reduction is an essential feature to reduce the complexity of the computations in the large data set environment. When handling large quantum of medical data set, as in the case like, Lung cancer prediction, based on symptoms and Risk factors, number of attributes/ dimensions pose a major challenge. Here in this study an attempt is made to(More)
Dimensionality reduction is generally carried out to reduce the complexity of the computations in the large data set environment by removing redundant or de-pendent attributes. For the Lung cancer disease prediction, in the pre-diagnosis stage, symptoms and risk factors are the main information carriers. Large number of symptoms and risk attributes poses(More)
An ontology is a formal and explicit specification of a shared conceptualization. Manual construction of domain ontology does not adequately satisfy requirements of new applications, because they need a more dynamic ontology and the possibility to manage a considerable quantity of concepts that humans cannot achieve alone. Researchers have discussed(More)
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