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Neighborhood Preserving Non-negative Tensor Factorization for image representation
2012 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2012Non-negative Matrix Factorization (NMF) has become a powerful tool for image representation due to its enhanced semantic interpretability under non-negativity. Unfortunately, two types of neighborhood information essential to representation are lost in NMF. For individual image, the local structure information is missing in the vectorization, which can
Yu-Xiong Wang +2 more
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A latent tensor factorization framework for non-negative convolutive models
2011 IEEE 19th Signal Processing and Communications Applications Conference (SIU), 2011Convolutive models emerge in various domains such as acoustics, image processing or seismic sciences. In this work, we investigate the convolutive models and the related deconvolution problems in a latent tensor factorization framework. We decrease the computational complexity of the inference scheme by utilizing the Fast Fourier Transform.
Umut Simsekli +2 more
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Classification of PolSAR image with non-negative tensor factorization approach
2016 IEEE International Geoscience and Remote Sensing Symposium (IGARSS), 2016Polarimetric synthetic aperture radar (PolSAR) is of great importance in the remote sensing, which can be used widely in both civil and military fields. However, existing classification methods cannot effectively utilize the spatial structure information of the SAR data.
Shuiping Gou +4 more
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Applying non-negative tensor factorization to centered data
Bankers, Markets & Investors, 2023Paul Fogel +3 more
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Hyperspectral Image Classification using Band-Group Non-negative Tensor Factorization
2018 4th Iranian Conference on Signal Processing and Intelligent Systems (ICSPIS), 2018In this paper, we propose a classification framework for 3D hyperspectral data. Discriminative features are extracted through applying Non-negative Tensor Factorization (NTF) technique to the image tensor. The factorized components indicate the spectral signatures and 2D abundance maps of the constituent materials. We use a composite kernel Multinomial
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Affective Color Palette Recommendations with Non-negative Tensor Factorization
2022 26th International Conference Information Visualisation (IV), 2022Ikuya Morita +3 more
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Multi-way Clustering Using Super-Symmetric Non-negative Tensor Factorization
2006We consider the problem of clustering data into k ≥ 2 clusters given complex relations — going beyond pairwise — between the data points. The complex n-wise relations are modeled by an n-way array where each entry corresponds to an affinity measure over an n-tuple of data points.
Amnon Shashua, Ron Zass, Tamir Hazan
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Novel Multi-layer Non-negative Tensor Factorization with Sparsity Constraints
2007In this paper we present a new method of 3D non-negative tensor factorization (NTF) that is robust in the presence of noise and has many potential applications, including multi-way blind source separation (BSS), multi-sensory or multi-dimensional data analysis, and sparse image coding.
Andrzej Cichocki +4 more
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