Results 231 to 240 of about 3,449 (252)

Wafer Pattern Recognition Using Tucker Decomposition

2019 IEEE 37th VLSI Test Symposium (VTS), 2019
In production test data analytics, it is often that an analysis involves the recognition of a conceptual pattern on a wafer map. A wafer pattern may hint a particular issue in the production by itself or guide the analysis into a certain direction. In this work, we introduce a novel approach to recognize patterns on a wafer map of pass/fail locations ...
Ahmed Wahba, Li-C. Wang, Zheng Zhang 0005, Nik Sumikawa   +3 more
openaire   +1 more source

Fast and Efficient Algorithms for Nonnegative Tucker Decomposition

2008
In this paper, we propose new and efficient algorithms for nonnegative Tucker decomposition (NTD): Fast i¾?-NTD algorithm which is much precise and faster than i¾?-NTD [1]; and β-NTD algorithm based on the βdivergence. These new algorithms include efficient normalization and initialization steps which help to reduce considerably the running time and ...
Anh Huy Phan 0001, Andrzej Cichocki
openaire   +1 more source

Quality assessment for color images with tucker decomposition

2012 19th IEEE International Conference on Image Processing, 2012
As an extension of the singular value decomposition based approaches, a novel metric based on Tucker decomposition for color image quality assessment is proposed in this paper. It extracts both the spacial and chromatic information of a color image with Tucker decomposition.
Cheng Cheng, Hanli Wang
openaire   +1 more source

Reduced-Complexity Singular Value Decomposition For Tucker Decomposition: Algorithm And Hardware

ICASSP 2020 - 2020 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2020
Tensors, as the multidimensional generalization of matrices, are naturally suited for representing and processing high-dimensional data. To date, tensors have been widely adopted in various data-intensive applications, such as machine learning and big data analysis.
Xiaofeng Hu, Chunhua Deng, Bo Yuan 0001
openaire   +1 more source

Local Learning Rules for Nonnegative Tucker Decomposition

2009
Analysis of data with high dimensionality in modern applications, such as spectral analysis, neuroscience, chemometrices naturally requires tensorial approaches different from standard matrix factorizations (PCA, ICA, NMF). The Tucker decomposition and its constrained versions with sparsity and/or nonnegativity constraints allow for the extraction of ...
Anh Huy Phan 0001, Andrzej Cichocki
openaire   +1 more source

Sparse Symmetric Format for Tucker Decomposition

IEEE Transactions on Parallel and Distributed Systems, 2023
Shruti Shivakumar, Jiajia Li 0001, Ramakrishnan Kannan, Srinivas Aluru   +3 more
openaire   +1 more source

Accurate regularized Tucker decomposition for image restoration

Applied Mathematical Modelling, 2023
Zhejun Huang, Wenwu Gong
exaly  

The correlation-based tucker decomposition for hyperspectral image compression

Neurocomputing, 2021
Zhibin Pan
exaly  

Infrared Small Target Detection via Nonconvex Tensor Tucker Decomposition With Factor Prior

IEEE Transactions on Geoscience and Remote Sensing, 2023
Wei An, Jungang Yang, Boyang Li
exaly  

TuckerMPI

ACM Transactions on Mathematical Software, 2020
Grey Ballard, Tamara Kolda
exaly