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sis of Higher Order Singular Value Decomposition
"... This work presents an analysis of Higher Order Singular Value Decomposition (HO-SVD) applied to lossy compression of 3D mesh animations. We describe strategies for choosing a number of preserved spatial and temporal components after tensor decomposition. Compression error is measured using three met ..."
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This work presents an analysis of Higher Order Singular Value Decomposition (HO-SVD) applied to lossy compression of 3D mesh animations. We describe strategies for choosing a number of preserved spatial and temporal components after tensor decomposition. Compression error is measured using three
Unfolding Higher Order Singular Value Decomposition). This
"... Abstract—We propose in this paper a new low rank filter ..."
The application of higher order singular value decomposition to independent component analysis
- In: SVD and signal processing III: algorithms, applications and architectures
, 1995
"... Abstr act − Two new generalizations of tenso r concepts for signa l processing are presented. These generalizatio ns are typically relev ant for appli cations where one tenso r consi sts of valua ble measured data or signa ls, that shoul d be retai ned, while the second tenso r conta ins data or inf ..."
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Cited by 2 (0 self)
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or information that shoul d be rejected. First the higher order singular value decomposition for a singl e tenso r is extended to pairs of tenso rs; this is the multi linear equiv alent of the generalized or quoti ent SVD (GSVD, QSVD) for pairs of matri ces. Next the notio n of oriented signa l-tosigna l ratio
Image Fusion Using Higher Order Singular Value Decomposition
"... Abstract — Image Fusion means the combining of two or more images into a single image that has the maximum information content without producing details that are not present in the original image. Image fusion method is in two groups –Spatial Domain Fusion and Transform domain fusion. We have used H ..."
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Higher order Singular value decomposition method for mage fusion technique.
Handwritten Digit Classification using Higher Order Singular Value Decomposition
"... In this paper we present two algorithms for handwritten digit classification based on the higher order singular value decomposition (HOSVD). The first algorithm uses HOSVD for construction of the class models and achieves classification results with error rate lower than 6%. The second algorithm use ..."
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Cited by 23 (2 self)
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In this paper we present two algorithms for handwritten digit classification based on the higher order singular value decomposition (HOSVD). The first algorithm uses HOSVD for construction of the class models and achieves classification results with error rate lower than 6%. The second algorithm
IMAGE FUSION USING HIGHER ORDER SINGULAR VALUE DECOMPOSITION
"... The goal of image fusion is to combine relevant information from two or more source images into one single image such that the single image contains as much information from all the source images as possible. There are many image fusion methods. This paper present some of the image fusion techniques ..."
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techniques for image fusion and propose novel higher order singular value decomposition (HOSVD) based image fusion algorithm. Image fusion depends on local information of source images, the proposed algorithm picks out informative image patches of source images to constitute the fused image by processing
ON HIGHER-ORDER SINGULAR VALUE DECOMPOSITION FROM INCOMPLETE DATA∗
"... Abstract. Higher-order singular value decomposition (HOSVD) is an efficient way for data reduction and also eliciting intrinsic structure of multi-dimensional array data. It has been used in many applications, and some of them involve incomplete data. To obtain HOSVD of the data with missing values, ..."
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Abstract. Higher-order singular value decomposition (HOSVD) is an efficient way for data reduction and also eliciting intrinsic structure of multi-dimensional array data. It has been used in many applications, and some of them involve incomplete data. To obtain HOSVD of the data with missing values
Using the Higher Order Singular Value Decomposition (HOSVD) for Video Denoising
"... We present an algorithm for denoising of videos corrupted by additive i.i.d. zero mean Gaussian noise with a fixed and known standard deviation. Our algorithm is patch-based. Given a patch from a frame in the video, the algorithm collects similar patches from the same and adjacent frames. All the pa ..."
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the patches in this group are denoised using a transform-based approach that involves hard thresholding of insignificant coefficients. In this paper, the transform chosen is the higher order singular value decomposition of the group of similar patches. This procedure is repeated across the entire video
Fractional order singular value decomposition representation for face recognition
- PATTERN RECOGNITION
, 2007
"... Face Representation (FR) plays a typically important role in face recognition and methods such as Principal Component Analysis (PCA) and Linear Discriminant Analysis (LDA) have been received wide attention recently. However, despite of the achieved successes, these FR methods will inevitably lead to ..."
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Cited by 3 (2 self)
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facial variations and on the other hand dominate the composition of the face image. Then based on these observations, we subtly deflate the weights of the facial variation sensitive base images by a parameter α and propose a novel Fractional order Singular Value Decomposition Representation (FSVDR
Towards MapReduce Algorithms for the Higher Order-Singular Value Decomposition
"... (Unterschrift des Kandidaten) ivZusammenfassung ..."
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