Results 21 to 30 of about 13,782,934 (217)
iScience, 2022 Summary: Symptoms of adverse reactions to vaccines evolve over time, but traditional studies have focused only on the frequency and intensity of symptoms.
Kei Ikeda +16 more
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Alzheimer’s Disease Recognition Applying Non-Negative Matrix Factorization Characteristics from Brain Magnetic Resonance Images (MRI) [PDF]
E3S Web of Conferences, 2023 To more accurately depict Alzheimer’s disease (AD) and projecting clinical outcomes while taking into account advancements in clinical imaging and substantial learning, several experts are gradually using ConvNet (CNNs) to remove deep intensity features ...
Reddy G. Vijendar +4 more
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Image Clustering Algorithm Based on Hypergraph Regularized Nonnegative Tucker Decomposition [PDF]
Jisuanji gongcheng, 2022 The internal geometry structure of high-dimensional data is ignored when nonnegative tensor decomposition is applied to image clustering.To solve this problem, we propose a Hypergraph regularized Nonnegative Tucker Decomposition(HGNTD) model by adding a ...
CHEN Luyao, LIU Qilong, XU Yunxia, CHEN Zhen
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Hyperspectral and Multispectral Image Fusion Using Coupled Non-Negative Tucker Tensor Decomposition
Remote Sensing, 2021 Fusing a low spatial resolution hyperspectral image (HSI) with a high spatial resolution multispectral image (MSI), aiming to produce a super-resolution hyperspectral image, has recently attracted increasing research interest.
Marzieh Zare +3 more
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Sparse Constrained Low Tensor Rank Representation Framework for Hyperspectral Unmixing
Remote Sensing, 2021 Recently, non-negative tensor factorization (NTF) as a very powerful tool has attracted the attention of researchers. It is used in the unmixing of hyperspectral images (HSI) due to its excellent expression ability without any information loss when ...
Le Dong, Yuan Yuan
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Research on Dynamic Topic Recognition Based on the Change of Word Co-Occurrence Frequency
Zhishi guanli luntan, 2022 [Purpose/Significance] The research on topic recognition is very important to clarify the knowledge structure and research hotspots in the field. Dynamic identification of domain topics can help researchers understand and master the development trend and
Xi Chongjun, Liu Wenbin, Ding Kai
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Non-negative Tensor Factorization for Speech Enhancement [PDF]
Proceedings of the 2016 International Conference on Artificial Intelligence: Technologies and Applications, 2016 This paper proposes an algorithm for speech enhancement by non-negative tensor factorisation. We group adjacent time-frequency matrices in the spectrograms together to form a tensor as a basic input in our algorithm. The non-negative tensor factorisation is followed to perform sound source separation between speeches and noises.
Mengnan Shi, Weiqiang Zhang, Liang He
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, 2010 This is the author's accepted pre-print of the article, first published as M. D. Plumbley, A. Cichocki and R. Bro. Non-negative mixtures. In P. Comon and C. Jutten (Ed), Handbook of Blind Source Separation: Independent Component Analysis and Applications.
M. D. Plumbley +9 more
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Simultaneous non-negative matrix factorization for multiple large scale gene expression datasets in toxiciology [PDF]
, 2012 Non-negative matrix factorization is a useful tool for reducing the dimension of large datasets. This work considers simultaneous non-negative matrix factorization of multiple sources of data.
Mudaliar, Manikhandan A. V. +7 more
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Weighted Group Sparsity-Constrained Tensor Factorization for Hyperspectral Unmixing
Remote Sensing, 2022 Recently, unmixing methods based on nonnegative tensor factorization have played an important role in the decomposition of hyperspectral mixed pixels.
Xinxi Feng, Le Han, Le Dong
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