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Fuzzy clustering algorithms for unsupervised change detection in remote sensing images
In this paper, we propose a context-sensitive technique for unsupervised change detection in multitemporal remote sensing images. The technique is based on fuzzy clustering approach and takes care ofExpand
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A Context-Sensitive Technique for Unsupervised Change Detection Based on Hopfield-Type Neural Networks
In this paper, we propose a context-sensitive technique for unsupervised change detection in multitemporal remote sensing images. This technique is based on a modified Hopfield neural networkExpand
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Robust global and local fuzzy energy based active contour for image segmentation
Graphical abstractDisplay Omitted HighlightsIt is very difficult to segment images having high intensity inhomogeneity.A global and local fuzzy energy based active contour is proposed to detectExpand
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An unsupervised context-sensitive change detection technique based on modified self-organizing feature map neural network
In this paper, we propose an unsupervised context-sensitive technique for change-detection in multitemporal remote sensing images. Here a modified self-organizing feature map neural network is used.Expand
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Fuzzy clustering algorithms incorporating local information for change detection in remotely sensed images
In this paper we have used two fuzzy clustering algorithms, namely fuzzy c-means (FCM) and Gustafson-Kessel clustering (GKC) along with local information for unsupervised change detection inExpand
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Semi-supervised change detection using modified self-organizing feature map neural network
In the present article, semi-supervised learning is integrated with an unsupervised context-sensitive change detection technique based on modified self-organizing feature map (MSOFM) network. In theExpand
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An architecture for next-generation radio access networks
With fourth-generation wireless technologies envisioned to provide high bandwidth for content-rich multimedia applications, next-generation mobile communication systems are well poised to lead theExpand
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A novel approach for change detection of remotely sensed images using semi-supervised multiple classifier system
In this article, a novel approach using ensemble of semi-supervised classifiers is proposed for change detection in remotely sensed images. Unlike the other traditional methodologies for detection ofExpand
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Change detection for moving object segmentation with robust background construction under Wronskian framework
Although background subtraction techniques have been used for several years in vision systems for moving object detection, many of them fail to provide good results in presence of noise, illuminationExpand
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Supervised and unsupervised landuse map generation from remotely sensed images using ant based systems
The landuse or land-cover map depicts the physical coverage of the Earth's terrestrial surface according to its use. Landuse map generation from remotely sensed images is one of the challenging tasksExpand
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