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With the continuous development of network and database technology, share and conversion on heterogeneous data are still a complex problem currently facing. Current methods are mostly based on the similarity between the field to complete the matching process, although this method can finish partial matches on information, its time complexity is very high due to the large processing data sets and the...
This paper presents a flexible shape-based texture analysis method by investigating the co-occurrence patterns of shapes. More precisely, a texture image is represented by a tree of shapes, each of which is associated with several attributes. The modeling of texture is thus converted to characterize the tree of shapes. To this aim, we first learn a set of co-occurrence patterns of shapes from texture...
Most previous approaches to automatic audio events (AEs) annotation are based on supervised learning which relies on the availability of a labeled corpus to train classification models. However, instance annotation is often difficult, expensive, and time consuming. In this paper, we apply semi-supervised learning with transductive Support Vector Machine (TSVM) algorithm to automatic AEs annotation...
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