نتایج جستجو برای: Berkley images dataset

تعداد نتایج: 344628  

2010
Ahmed R. Khalifa

One of the important problems that ever exist in performance evaluation of any segmentation algorithm is that, when we ingrain the obtained results in a specific application, these results may not be expandable to any other application. So, it is very difficult to appraise whether one algorithm produces more precise segmentation than the other one. This paper, presents a novel technique through...

Introduction: Age-related macular degeneration (AMD) is one of the major causes of visual loss among the elderly. It causes degeneration of cells in the macula. Early diagnosis can be helpful in preventing blindness. Drusen are the initial symptoms of AMD. Since drusen have a wide variety, locating them in screening images is difficult and time-consuming. An automated digital fundus photography...

Journal: :CoRR 2013
Somayeh Danafar Paola M. V. Rancoita Tobias Glasmachers Kevin Whittingstall Jürgen Schmidhuber

Do two data samples come from different distributions? Recent studies of this fundamental problem focused on embedding probability distributions into sufficiently rich characteristic Reproducing Kernel Hilbert Spaces (RKHSs), to compare distributions by the distance between their embeddings. We show that Regularized Maximum Mean Discrepancy (RMMD), our novel measure for kernel-based hypothesis ...

This paper deals with the problem of face recognition from a single image per person by producing virtual images using neural networks. To this aim, the person and variation information are separated and the associated manifolds are estimated using a nonlinear neural information processing model. For increasing the number of training samples in neural classifier, virtual images are produced for...

Journal: :International Journal of Computer Vision 2020

Image segmentation is a fundamental step in many of image processing applications. In most cases the image’s pixels are clustered only based on the pixels’ intensity or color information and neither spatial nor neighborhood information of pixels is used in the clustering process. Considering the importance of including spatial information of pixels which improves the quality of image segmentati...

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