Results 41 to 50 of about 55,457 (295)
ShinyButchR: Interactive NMF-based decomposition workflow of genome-scale datasets
Biology Methods and Protocols, 2020 Non-negative matrix factorization (NMF) has been widely used for the analysis of genomic data to perform feature extraction and signature identification due to the interpretability of the decomposed signatures.
Andrés Quintero +10 more
semanticscholar +1 more source
ComTech, 2012 NMF is one new developed method to make the part-based representation of non-negative data, such as human face image. NMF can reduce the dimension of high dimensional data such as multimedia data. In many researches,NMF can also used as a classification
William Salim
doaj +1 more source
Clustering NMF basis functions using Shifted NMF for monaural sound source separation
2011 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2011 Non-negative Matrix Factorization (NMF) has found use in single channel separation of audio signals, as it gives a parts-based decomposition of audio spectrograms where the parts typically correspond to individual notes or chords. However, a notable shortcoming of NMF is the need to cluster the basis functions to their sources after decomposition ...
Jaiswal, Rajesh +4 more
openaire +3 more sources
Nonconvex Nonseparable Sparse Nonnegative Matrix Factorization for Hyperspectral Unmixing
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2020 Hyperspectral unmixing is an important step to learn the material categories and corresponding distributions in a scene. Over the past decade, nonnegative matrix factorization (NMF) has been utilized for this task, thanks to its good physical ...
Fengchao Xiong +3 more
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Cluster-Wise Weighted NMF for Hyperspectral Images Unmixing with Imbalanced Data
Remote Sensing, 2021 Hyperspectral unmixing is an important technique for analyzing remote sensing images which aims to obtain a collection of endmembers and their corresponding abundances.
Xiaochen Lv, Wenhong Wang, Hongfu Liu
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Underwater acoustic target signal enhancement algorithm optimized by feature preservation and noise update [PDF]
Zhihui kongzhi yu fangzhenThe enhancement effect of the classic Nonnegative Matrix Factorization (NMF) applied to underwater acoustic target signal is unsatisfactory for the feature overlap of underwater acoustic target signal and the variability of ocean underwater acoustic ...
XIAO Haixia, CUI Shuangyue, LI Dawei, SUN Mingming, LIU Xianzhong, YANG Zhenxin
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Generalized Separable Nonnegative Matrix Factorization
, 2019 Nonnegative matrix factorization (NMF) is a linear dimensionality technique for nonnegative data with applications such as image analysis, text mining, audio source separation and hyperspectral unmixing.
Gillis, Nicolas, Pan, Junjun
core +1 more source
Robust Semi-Supervised Non-Negative Matrix Factorization With Structured Normalization
IEEE Access, 2019 Non-negative matrix factorization (NMF) approximates a non-negative data matrix with the product of two low-rank non-negative matrices by minimizing the cost of such approximation.
Liujing Wang +4 more
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Knowledge Discovery Through Topic Modeling on GoPartner User Reviews Using BERTopic, LDA, and NMF
Journal of Applied Informatics and ComputingTransportation and food delivery services are one of the driving sectors of the digital economy in Indonesia. The e-Conomy SEA 2023 report shows that the transportation and food delivery services sector experienced a decrease in GMV in 2023 by 8% from ...
Metti Detricia Pratiwi, Ken Ditha Tania
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BioMedical Engineering OnLine, 2020 Background Nonnegative matrix factorization (NMF) has been successfully used for electroencephalography (EEG) spectral analysis. Since NMF was proposed in the 1990s, many adaptive algorithms have been developed.
Guoqiang Hu +6 more
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