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Image classification is an important task for many aspects of global change studies and environmental applications. This paper emphasizes on the analysis and usage of different advanced image classification techniques like Cloud Basis Functions (CBFs) Neural Networks, Artificial Neural Networks (ANN) and Support Vector Machines (SVM) for object based classification to get better accuracy. For comparison,...
This study focuses on segmentation and validation of brain MR images. Artificial neural network (ANN) has been applied to obtain the targeted segments from these images. In preprocessing step for avoiding the chances of misclassification during training of ANN, the unwanted skull tissues were removed by employing active contour modeling (ACM). The removal of these tissues leaves an image containing...
One of the basic challenges to robust iris recognition is iris segmentation. To represent the iris, some researchers fit circles, ellipses or active contours to the boundary pixels of the segmented iris. In order to get an accurate fit, the iris boundary must first be accurately identified. Some segmentation methods operate on a pre-processed gray-scaled image, while others use a thresholded binary...
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