with quick development of digital images and the availability of imaging tools, massive amounts of images are created. therefore, efficient management and suitable retrieval, especially by computers, is one of themost challenging fields in image processing. automatic image annotation (aia) or refers to attaching words, keywords or comments to an image or to a selected part of it. in this paper,...

With quick development of digital images and the availability of imaging tools, massive amounts of images are created. Therefore, efficient management and suitable retrieval, especially by computers, is one of themost challenging fields in image processing. Automatic image annotation (AIA) or refers to attaching words, keywords or comments to an image or to a selected part of it. In this paper,...

For classifying time series, a nearest-neighbor approach is widely used in practice with performance often competitive with or better than more elaborate methods such as neural networks, decision trees, and support vector machines. We develop theoretical justification for the effectiveness of nearest-neighbor-like classification of time series. Our guiding hypothesis is that in many application...

For some applications of k-nearest neighbor classiiers, the best results are obtained at a relatively large value of k. With the majority voting method, these results can be suboptimal. In this paper the performance of various weighted voting methods is tested on a number of machine learning datasets. The results show that weighted voting is often superior to majority voting, and that the linea...

ARTICLE HISTORY: Received 01 January 2016 Revised 12 June 2016 Accepted 13 June 2016 With quick development of digital images and the availability of imaging tools, massive amounts of images are created. Therefore, efficient management and suitable retrieval, especially by computers, is one of the most challenging fields in image processing. Automatic image annotation (AIA) or refers to attachi...

Despite the popularity and empirical success of patch-based nearest-neighbor and weighted majority voting approaches to medical image segmentation, there has been no theoretical development on when, why, and how well these nonparametric methods work. We bridge this gap by providing a theoretical performance guarantee for nearest-neighbor and weighted majority voting segmentation under a new pro...

To improve the accuracy of data classification systems, several techniques using classifier fusion have been suggested. This paper proposed a model of classifier fusion for character recognition problem. The work presented here aims to tackle the disadvantages and benefit of different classifiers with varying feature sets. In particular, this approach proposes the use of statistical procedures ...