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Automatic image classification is a challenging research topic in Web image mining. In this paper, we formulate image classification problem as the calculation of the distance measure between training manifold and test manifold. We propose an improved nonlinear dimensionality reduction algorithm based on neighborhood optimization, not only to decrease feature dimensionality but also to transform the...
The planted acreage estimation for major crops by using remote sensing is typically combine the sample data from ground survey with information derived from image classification, and the common applied approaches are regression estimator by using linear model and calibration estimator by using confusion matrix. In general, the crop acreage estimation for provincial level in China only satisfied the...
To solve the two-class classification problem existing in semantic-based image understanding, a novel classification method based on double manifold learning is proposed, which can transform the classification problem from a high-dimensional data space to a feature space with lower dimensionality. Two manifolds with different intrinsic dimensionalities will be first established separately, according...
Image classification is one of the important parts of digital image processing. We propose a novel feature space-based image classification method by combining manifold learning and mixture model. In this paper, the process of image classification can be viewed as two parts: a coarse-grained classification and a fine-grained classification. In the coarse-grained classification, we apply the ISOMAP...
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