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In memory based learning algorithm, K-nearest neighbour method used for classification and clustering problems. Using K-NN algorithm we can define the class of an unknown sample data based on the prior learning of the system. In this paper we will be looking over a classification problem and will present a solution to enhance the accuracy and performance of K-NN algorithm.
Non-destructive phenotyping of earthworms by digital imaging and image analysis is the novel concept being proposed and explored in this paper. Earthworms are very important component of plant soil interaction via rhizosphere. Although a lot of research resources have been applied to phenotying roots by image analysis, there has been practically insignificant work on phenotying earthworms by image...
Resolution plays a crucial role for study of information in an image. Therefore to enhance the resolution of an image, there are so many techniques have been proposed with respect to the reference images. In this paper, we proposed a new scheme for single image super-resolution based on the neighbor embedding method. Many feature selection methods have been proposed for the learning based super-resolution...
In this paper a method for automatic detection of root crowns in root images, are designed, implemented and quantitatively compared. The approach is based on the theory of statistical learning. The root images are preprocessed with algorithms for intensity normalization, segmentation, edge detection and scale space corner detection. The features used in the experiments are the Zernike moments of the...
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