Zobrazeno 1 - 10
of 79
pro vyhledávání: '"Keyvanpour, Mohammadreza"'
Publikováno v:
International Journal of Machine Learning and Computing vol. 2, no. 3, pp. 257-260, 2012
In recent years, the management and processing of data streams has become a topic of active research in several fields of computer science such as, distributed systems, database systems, and data mining. A data stream can be thought of as a transient
Externí odkaz:
http://arxiv.org/abs/1208.0684
Publikováno v:
International Journal of Advanced Engineering Sciences and Technologies, Vol No. 4, Issue No. 2, 014 - 017, 2011
Understanding the structure and dynamics of biological networks is one of the important challenges in system biology. In addition, increasing amount of experimental data in biological networks necessitate the use of efficient methods to analyze these
Externí odkaz:
http://arxiv.org/abs/1207.3543
Autor:
Keyvanpour, Mohammadreza, Tavoli, Reza
Publikováno v:
International Journal of Computer Science Issues, Vol 9, Issue 3, No 3 (2012) 125-130
Feature weighting is a technique used to approximate the optimal degree of influence of individual features. This paper presents a feature weighting method for Document Image Retrieval System (DIRS) based on keyword spotting. In this method, we weigh
Externí odkaz:
http://arxiv.org/abs/1206.1291
Publikováno v:
International Journal of Computer Science Issues, Vol. 8, Issue 5, No 1 (2011) 42-48
One of the important requirements in image retrieval, indexing, classification, clustering and etc. is extracting efficient features from images. The color feature is one of the most widely used visual features. Use of color histogram is the most com
Externí odkaz:
http://arxiv.org/abs/1201.3337
Publikováno v:
Advances in information Sciences and Service Sciences(AISS),Volume 3, Number 9, October 2011, 229-236
Leveraging the power of increasing amounts of data to analyze customer base for attracting and retaining the most valuable customers is a major problem facing companies in this information age. Data mining technologies extract hidden information and
Externí odkaz:
http://arxiv.org/abs/1201.1670
Publikováno v:
International Journal of Engineering Science and Technology, Vol. 3 No. 9 September 2011, 7211-7217
Scene mining is a subset of image mining in which scenes are classified to a distinct set of classes based on analysis of their content. In other word in scene mining, a label is given to visual content of scene, for example, mountain, beach. Scene m
Externí odkaz:
http://arxiv.org/abs/1201.1668
Publikováno v:
The International Journal of Multimedia & Its Applications (IJMA) Vol.3, No.1, February 2011
Due to the advances in hardware technology and increase in production of multimedia data in many applications, during the last decades, multimedia databases have become increasingly important. Contentbased multimedia retrieval is one of an important
Externí odkaz:
http://arxiv.org/abs/1105.1948
Publikováno v:
International Journal of Engineering Science and Technology (IJEST)Vol. 3 No. 3 Mar 2011
A growing number of applications that generate massive streams of data need intelligent data processing and online analysis. Real-time surveillance systems, telecommunication systems, sensor networks and other dynamic environments are such examples.
Externí odkaz:
http://arxiv.org/abs/1105.1950
Publikováno v:
International Journal on Computer Science and Engineering (IJCSE)Vol. 3 No. 2 Feb 2011
In recent years, the data mining techniques have met a serious challenge due to the increased concerning and worries of the privacy, that is, protecting the privacy of the critical and sensitive data. Different techniques and algorithms have been alr
Externí odkaz:
http://arxiv.org/abs/1105.1945
Publikováno v:
International Journal of Web & Semantic Technology (IJWesT), Vol. 2, No. 2, pp. 27-38, Aprill 2011
The Semantic Web is an extension of the current web in which information is given well-defined meaning. The perspective of Semantic Web is to promote the quality and intelligence of the current web by changing its contents into machine understandable
Externí odkaz:
http://arxiv.org/abs/1104.4950