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Foreground detection is a challenging problem in complex scenes. In this paper, a novel foreground detection method is proposed which combines background subspace learning with object smoothing model. Considering background scenes in consecutive frames are almost the same, they are approximated using an efficient subspace learning technique which is based on 2D images. Due to the pixels of objects...
This paper presents algorithms for biomedical video denoising using real-valued side information. In certain clinical settings, side information correlated to the underlying motion under imaging is available and can be used to infer motion and act as a global constraint for image denoising. Our methods assume the input data are noisy samples that lie on or near an image manifold parameterized by the...
The potential of artificial neural network (ANN) as a way for the nondestructive variety discrimination of fragrant mushrooms was evaluated. First, the visual and near infrared spectral data were analyzed by principal components analysis (PCA) for space clustering. The principal components (PCs) containing the main information of original spectra were picked out as the inputs of BP-ANN with three...
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