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Many elderly prefer to live independently at their own homes. However, how to use modern technologies to ensure their safety presents vast challenges and opportunities. Being able to non-intrusively sense the activities performed by the elderly definitely has great advantages in various circumstances. Non-intrusive activity recognition can be performed using the embedded sensors in modern smartphones...
Subspace methods have attracted increasing attention for visual tracking. However, most previous work only aim to pursuit the subspace basis to represent appearances, thus cannot reveal the rich structure information in real world videos. This paper proposes a guided low-rank subspace learning framework to simultaneously extract the orthogonal subspace basis, the low-rank coefficients and the sparse...
In this paper, we propose an effective approach to semi-supervised classification through kernel-based sparse representation. The new method computes the sparse representation of data in the feature space, and then the learner is subject to a cost function which aims to preserve the sparse representing coefficients. By mapping the data into the feature space, the so-called “l 2 -norm problem”...
Fisher criterion is one of most widely used methods for supervised feature selection. Traditional Fisher based feature selection methods focus on maximizing the distances inter-class and minimizing the distances of samples within the same class. But, they ignore the geometric structure of data in measuring the importance of the features. In this paper, we propose a new semi-supervised feature selection...
Acreage of crops is an important agricultural economic information. In this paper, Using a detailed land use data, constructed sample frame. Ditch planted crops into account the direction,. In support of GIS spatial technology, the survey cost and distribution of natural land, set a reasonable standard of land area. Then under the irregular block size, spatial distribution, the relationship between...
A novel images fusion method based on bidimensional empirical mode decomposition (BEMD) is proposed, aiming at solving the fusion problem of multi-focus images. BEMD is a new form of fully two-dimensional multi-scale decomposition and has superior quality in extracting salient features in multi-focus images. This paper uses BEMD to decompose the source images into their components adaptively without...
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