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Feature selection is considered to be an important step in the analysis of transcriptomes or gene expression data. Carrying out feature selection reduces the curse of the dimensionality problem and improves the interpretability of the problem. Numerous feature selection methods have been proposed in the literature and these methods rank the genes in order of their relative importance. However, most...
Recognition of object categories from their images is extremely challenging due to the large intra-class variations, and variations in pose, illumination and scale, in addition to lack of depth information of the object. Recovering the depth information from multiple images or from image cues such as variations in illumination or focus, is both computationally intensive and error prone. In contrast,...
The ever-increasing gigantic amount of images over the Web necessitates automatic schemes for meta-tagging content descriptions such as object categories. These meta-tags are essential to text-based image search engines to improve their search relevance. Traditional supervised scheme is not suitable for this task because it needs too much manual labelling efforts and yet is hard to scale to a large...
This paper presents the sensitivity analysis of a new technique for automated classification of human hand gestures based on Hu moments for robotics applications. It uses view-based approach for representation, and statistical technique for classification. This approach uses a cumulative image-difference technique where the time between the sequences of images is implicitly captured in the representation...
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