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65 articles for “Unsupervised”
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Representative Feature Selection for Efficient Clustering
Abstract: AbstractClustering is one of the widely used data mining techniques. In machine learning, it is an unsupervised learning method that needs training data to be used. The problem with clustering is that it is computationally expensive and takes more time for grouping high-dimensional data. Therefore it is necessary to reduce number of features in the high-dimensional data in order to make the search space reduced. Many techniques came into existance …
Published in Journal Of Network security · Vol. 5, Issue 2, 2017 · pp. 19–27 Read article
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Segmentation Methods for Images: A Systematic Review
Abstract: Image segmentation is the initial operation in image processing and computer vision to extract a region of interest from a still image or a sequence of images (video). Segmentation is the key operation to perform a number of applications today. Different supervised and unsupervised evaluation methods have been used for segmentation for numerous applications, but still it is a challenging task to identify which method is more accurate. This paper …
Published in Journal of Remote Sensing & GIS · Vol. 4, Issue 3, 2013 · pp. 61–67 Read article
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Identifying Trends in Landuse/Landcover Changes in Hisar Tehsil: A LCM Based Approach
Abstract: Land is a source of all basic human needs, (e.g., agriculture, forest, water supply etc.) which is being continuously depleted by various agents. Urban growth and urbanization are considered as one of the major factors responsible for change in landcover dynamics and depletion of land resources. As compared with other landcover classes such as agricultural land, urban land has smaller area coverage but its impact to the surrounding environment is …
Published in Journal of Remote Sensing & GIS · Vol. 8, Issue 1, 2017 · pp. 1–8 Read article
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A Machine Learning Approach for Investigating Spatial Structures between Spectral line Sources: Formaldehyde Absorptions versus Methanol Masers
Abstract: In this paper the authors present fascinating ideas on using machine learning algorithms to study connections in spatial distributions between observed spectral line sources. The method has been illustrated using observations of 4.8 GHz formaldehyde absorptions and 6.7 GHz methanol masers in the Galaxy. Both spectral line features have been well-observed in close associations with galactic star-formation regions, and we initiate this study to understand spatial connections between them. We …
Published in Research & Reviews : Journal of Space Science & Technology · Vol. 2, Issue 2, 2013 · pp. 1–11 Read article
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Automated Vessel Segmentation of Retinal Vessels using Hybrid Region Information
Abstract: AbstractRecent researches state that the categorization of retinal vessels into artery/vein (A/V) is a critical phase for automating the detection of vascular adjustments and for the calculation of function symptoms related to numerous systemic illnesses which includes diabetes, high blood pressure, and different cardiovascular situations. This paper affords an automatic method for A/V class, primarily based on the evaluation of a graph extracted from the retinal vasculature. The proposed method …
Published in Research & Reviews : Journal of Statistics · Vol. 7, Issue 3, 2018 · pp. 28–36 Read article