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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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To get full information or details of source code for pose invariant face recognition please have a look on the pages

http://seminarsprojects.net/Thread-face-recognition-report?pid=45931&mode=threaded

http://seminarsprojects.net/Thread-face-recognition

http://seminarsprojects.net/Thread-face-recognition-using-laplacianfaces--25370?pid=53072&mode=threaded

if you again feel trouble on source code for pose invariant face recognition please reply in that page and ask specific fields in source code for pose invariant face recognition ....etc

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Abstract:
This paper presents an approach for integrating e-learning with the traditional education system. A conceptual map is then created for this integration leading to a functional model for open and flexible learning. In the proposed integration, convergence of CD-based, class based and web based education in recommended and architecture to achieve this convergence is presented. In order to transform the existing schools, colleges and universities into digital campuses, an inclusive system architecture is designed for digital campus. A c ....etc

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Demand for the research and development of the micro-manufacturing technologies is being fueled by the ever-increasing trend towards miniaturization over a wide spectrum of disciplines and industries. Recent technological advancement in the defense, biomedical, telecom-munications, consumer electronics have spearheaded the need for micromanufacturing technology, which is now beginning to find application in the automotive and aerospace industries due to the economic potential of the micro-factory paradigm. Micro-scale mechanical manufacturing p ....etc

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We present a new unsupervised algorithm to discover and segment out common objects from large and diverse image collections. In contrast to previous co-segmentation methods, our algorithm performs well even in the presence of significant amounts of noise images (images not containing a common object), as typical for datasets collected from Internet search. The key insight to our algorithm is that common object patterns should be salient within each image, while being sparse with respect to smooth transformations across other images. We propose ....etc

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Unsupervised Learning of Probabilistic Object Models


INTRODUCTION
RECENT work on object classification and recognition has
tended to represent objects in terms of spatial configurations
of features at a small number of interest points ,
, , , , . Such models are computationally efficient,
for both learning and inference, and can be very effective for
tasks such as classification. But they have two major
disadvantages: 1) the sparseness of their representations
re ....etc

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COMPUTATIONALLY EFFICIENT SERIAL COMBINATION OF ROTATION-INVARIANT AND ROTATION COMPENSATING IRIS RECOGNITION ALGORITHMS
Abstract:
Rotation compensation is one of the computational bottlenecks in large scale iris-based identification schemes, since a significant amount of Hamming distance computations is required in a single match due to the necessary shifting of the iris codes to compensate for eye tilt. To cope with this problem, a serial classifier combination approach is proposed for iris-based identification, combining rot ....etc

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pls sent about analysis of quality of object oriented systems using object oriented metrics ppt
thanku. ....etc

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