to get information about the topic supervised learning of semantic classes for image annotation and retrieval full report ppt and related topic refer the page link bellow
http://seminarsprojects.net/Thread-supervised-learning-of-semantic-classes-for-image-anotation-and-retrieval ....etc

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matlab code for semi supervised margin analysis image retrieval ....etc

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Abstract

Microarray technology is one of the important biotechnological means that allows to record the expression levels of thousands of genes simultaneously within a number of different samples. An important application of microarray gene expression data in functional genomics is to classify samples according to their gene expression profiles. Among the large amount of genes presented in gene expression data, only a small fraction of them is effective for performing a certain diagnostic test. Hence, one of the major tasks with the gene expre ....etc

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In mathematics and computer science, graph theory is the study of graphs, which are mathematical structures used to model pairwise relations between objects. A graph in this context is made up of vertices, nodes, or points which are connected by edges, arcs, or lines. A graph may be undirected, meaning that there is no distinction between the two vertices associated with each edge, or its edges may be directed from one vertex to another; see Graph (discrete mathematics) for more detailed definitions and for other variations in the types of grap ....etc

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tracking mobile users in wireless networks via semi supervised colocalization ppt

Abstract

Recent years have witnessed the growing popularity of sensor and sensor-network technologies, supporting important practical applications. One of the fundamental issues is how to accurately locate a user with few labeled data in a wireless sensor network, where a major difficulty arises from the need to label large quantities of user location data, which in turn requires knowledge about the locations of signal transmitters or access points. To solve thi ....etc

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A kernel is the core component of every computer operating system. While kernels are highly technical in nature, and may be hidden from the user under many layers of software and applications, they do have distinguishing or characteristic features, such as computer architecture, design goals, as well as the more practical features that they provide. A direct comparison of operating system kernels can highlight these design choices, and provide insight into different niches and the evolving technology of kernels ....etc

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Abstract In this paper, we present a novel framework, called learning by propagability, for two essential data mining tasks, i.e., classification and regression. The whole learning process is driven by the philosophy that the data labels and the optimal feature representation jointly constitute a harmonic system, where the data labels are invariant with respect to the propagation on the similarity graph constructed based on the optimal feature representation. Based on this philosophy, a unified framework of learning by propagability is propose ....etc

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presented by:
Rahul Kala

Abstract
Graphs find a variety of use in numerous domains especially because of their capability to model common problems. The social networking graphs that are used for social networking analysis, a feature given by various social networking sites are an example of this. Graphs can also be visualized in the search engines to carry search operations and provide results. Various searching algorithms have been developed for searching in graphs. In this paper we propose that the entire network graph be ....etc

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request to send ppt of semi supervised clustering with multi viewpoint based similarity measure ....etc

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Abstract A probabilistic formulation for semantic image annotation and retrieval is proposed. Annotation and retrieval are posed as
classification problems where each class is defined as the group of database images labeled with a common semantic label. It is
shown that, by establishing this one-to-one correspondence between semantic labels and semantic classes, a minimum probability of
error annotation and retrieval are feasible with algorithms that are 1) conceptually simple, 2) computationally efficient, and 3) do not
require prior sema ....etc

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