There are numerous methods to classification of feature types. Imagine provides classification models in addition to texture features and convolution methods that assist in detecting various feature types. Using ESRI's ArcView and ArcGIS Feature Analyst extension, the process of feature extraction is readily accessible and user-friendly to the analyst. But, in general, road detection, specifica...

Biomass represents an extremely valuable potential to obtain new clean energy sources and natural structurally complex bioactive compounds. Renewable energy can be produced from any biological feedstock, that contains appreciable amounts of sugar or materials that can be converted into sugar (e.g. starch or cellulose). Lignocellulose’s biomass–dendromass and phytomass is natural based material ...

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Feature Extraction is significant for determining security vulnerabilities in software. Mining closed sequential patterns provides complete and condensed information for non-redundant frequent sequences generation. In this paper, we discuss the feature interaction problem and propose an efficient algorithm to extract features in vulnerability sequences. Each closed sequential pattern represents...

In this paper we present dRAP-Independent, an algorithm for independent distributed mining of first-order frequent patterns. This system is based on RAP, an algorithm for finding maximal frequent patterns in first-order logic. dRAPIndependent utilizes a modified data partitioning schema introduced by Savasere et al. and offers good performance and low communication overhead. We analyze the perf...

In recent years, many applications dealing with data generated continuously and at high speeds have emerged. These data are now quali ed as data streams. Dealing with potentially in nite quantities of data imposes constraints that raise many processing problems. As an example of such constraints we have the inability to block the data stream as well as the need to produce results in real time. ...