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Wyświetlanie 1-10 z 13
Tytuł:
Moving cast shadow detection using block nonnegative matrix factorization
Autorzy:
Yang, X.
Liu, D.
Zhou, D.
Yang, R.
Powiązania:
https://bibliotekanauki.pl/articles/200448.pdf
Data publikacji:
2018
Wydawca:
Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:
moving cast shadow detection
video surveillance
nonnegative matrix factorization
block nonnegative matrix factorization
nadzór wideo
nieujemna faktoryzacja macierzy
Opis:
In recent years, moving cast shadow detection has become a critical challenge in improving the accuracy of moving object detection in video surveillance. In this paper, we propose two novel moving cast shadow detection methods based on nonnegative matrix factorization (NMF) and block nonnegative matrix factorization (BNMF). First, the algorithm of moving cast shadow detection using NMF is given and the key points such as the determination of moving shadow areas and the choice of discriminant function are specified. Then BNMF are introduced so that the new training samples and new classes can be added constantly with lower computational complexity. Finally, the improved shadow detection method is detailed described according to BNMF. The effectiveness of proposed methods is evaluated in various scenes. Experimental results demonstrate that the method achieves high detection rate and outperforms several state-of-the-art methods.
Źródło:
Bulletin of the Polish Academy of Sciences. Technical Sciences; 2018, 66, 2; 229-234
0239-7528
Pojawia się w:
Bulletin of the Polish Academy of Sciences. Technical Sciences
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Multiplicative Algorithm for Correntropy-Based Nonnegative Matrix Factorization
Autorzy:
Hosseini-Asl, E.
Zurada, J. M.
Powiązania:
https://bibliotekanauki.pl/articles/108758.pdf
Data publikacji:
2013
Wydawca:
Społeczna Akademia Nauk w Łodzi
Tematy:
Nonnegative Matrix Factorization (NMF)
Correntropy
Multiplicative Algorithm
Document Clustering
Opis:
Nonnegative matrix factorization (NMF) is a popular dimension reduction technique used for clustering by extracting latent features from highdimensional data and is widely used for text mining. Several optimization algorithms have been developed for NMF with different cost functions. In this paper we evaluate the correntropy similarity cost function. Correntropy is a nonlinear localized similarity measure which measures the similarity between two random variables using entropy-based criterion, and is especially robust to outliers. Some algorithms based on gradient descent have been used for correntropy cost function, but their convergence is highly dependent on proper initialization and step size and other parameter selection. The proposed general multiplicative factorization algorithm uses the gradient descent algorithm with adaptive step size to maximize the correntropy similarity between the data matrix and its factorization. After devising the algorithm, its performance has been evaluated for document clustering. Results were compared with constrained gradient descent method using steepest descent and L-BFGS methods. The simulations show that the performance of steepest descent and LBFGS convergence are highly dependent on gradient descent step size which depends on σ parameter of correntropy cost function. However, the multiplicative algorithm is shown to be less sensitive to σ parameterand yields better clustering results than other algorithms. The results demonstrate that clustering performance measured by entropy and purity improve the clustering. The multiplicative correntropy-based algorithm also shows less variation in accuracy of document clusters for variable number of clusters. The convergence of each algorithm is also investigated, and the experiments have shown that the multiplicative algorithm converges faster than L-BFGS and steepest descent method.
Źródło:
Journal of Applied Computer Science Methods; 2013, 5 No. 2; 89-104
1689-9636
Pojawia się w:
Journal of Applied Computer Science Methods
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Projective nonnegative matrix factorization based on α-divergence
Autorzy:
Yang, Z.
Oja, E.
Powiązania:
https://bibliotekanauki.pl/articles/91672.pdf
Data publikacji:
2011
Wydawca:
Społeczna Akademia Nauk w Łodzi. Polskie Towarzystwo Sieci Neuronowych
Tematy:
Nonnegative Matrix Factorization
NMF
α-divergence
PNMF
α-NMF
α-PNMF
Opis:
The well-known Nonnegative Matrix Factorization (NMF) method can be provided with more flexibility by generalizing the non-normalized Kullback-Leibler divergence to α- divergences. However, the resulting α-NMF method can only achieve mediocre sparsity for the factorizing matrices. We have earlier proposed a variant of NMF, called Projective NMF (PNMF) that has been shown to have superior sparsity over standard NMF. Here we propose to incorporate both merits of α-NMF and PNMF. Our α-PNMF method can produce a much sparser factorizing matrix, which is desired in many scenarios. Theoretically, we provide a rigorous convergence proof that the iterative updates of α-PNMF monotonically decrease the α-divergence between the input matrix and its approximate. Empirically, the advantages of α-PNMF are verified in two application scenarios: (1) it is able to learn highly sparse and localized part-based representations of facial images; (2) it outperforms α-NMF and PNMF for clustering in terms of higher purity and smaller entropy.
Źródło:
Journal of Artificial Intelligence and Soft Computing Research; 2011, 1, 1; 7-16
2083-2567
2449-6499
Pojawia się w:
Journal of Artificial Intelligence and Soft Computing Research
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Stabilization of an epidemic model via an N-periodic approach
Autorzy:
Cantó, B.
Coll, C.
Sánchez, E.
Powiązania:
https://bibliotekanauki.pl/articles/330825.pdf
Data publikacji:
2018
Wydawca:
Uniwersytet Zielonogórski. Oficyna Wydawnicza
Tematy:
nonnegative matrix
reducible matrix
seasonality
epidemic process
macierz nieujemna
macierz redukowalna
proces epidemiczny
Opis:
We analyze the evolution of an infectious disease by combining different groups of a population when the route of transmission is via encounters with free-living virulent organisms that can survive for a long time outside the individual. This study involves matrix analysis of lower triangular block matrices and some of their spectral properties. We propose an N-periodic control strategy in order to stabilize the disease around the disease-free equilibrium point.
Źródło:
International Journal of Applied Mathematics and Computer Science; 2018, 28, 1; 185-195
1641-876X
2083-8492
Pojawia się w:
International Journal of Applied Mathematics and Computer Science
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Factorization of Nonnegative Matrices by the Use of Elementary Operation
Autorzy:
Kaczorek, T.
Powiązania:
https://bibliotekanauki.pl/articles/386810.pdf
Data publikacji:
2012
Wydawca:
Politechnika Białostocka. Oficyna Wydawnicza Politechniki Białostockiej
Tematy:
faktoryzacja
nieujemna macierz
procedura
obliczanie
factorization
nonnegative matrix
positive rank
procedure
computation
Opis:
A method based on elementary column and row operations of the factorization of nonnegative matrices is proposed. It is shown that the nonnegative matrix R×( ? ) has positive full column rank if and only if it can be transformed to a matrix with cyclicstructure. A procedure for computation of nonnegative matrices ? R ×, ? R × ( ? rank (,)) satisfying = is proposed.
Źródło:
Acta Mechanica et Automatica; 2012, 6, 4; 15-18
1898-4088
2300-5319
Pojawia się w:
Acta Mechanica et Automatica
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Speech Enhancement Based on Discrete Wavelet Packet Transform and Itakura-Saito Nonnegative Matrix Factorisation
Autorzy:
Liu, Houguang
Wang, Wenbo
Xue, Lin
Yang, Jianhua
Wang, Zhihua
Hua, Chunli
Powiązania:
https://bibliotekanauki.pl/articles/1448505.pdf
Data publikacji:
2020
Wydawca:
Polska Akademia Nauk. Czasopisma i Monografie PAN
Tematy:
speech enhancement
discrete wavelet packet transform
nonnegative matrix factorisation
Itakura-Saito divergence
Opis:
Nonnegative matrix factorization (NMF) is one of the most popular machine learning tools for speech enhancement (SE). However, there are two problems reducing the performance of the traditional NMF-based SE algorithms. One is related to the overlap-and-add operation used in the short time Fourier transform (STFT) based signal reconstruction, and the other is the Euclidean distance used commonly as an objective function; these methods can cause distortion in the SE process. In order to get over these shortcomings, we propose a novel SE joint framework which combines the discrete wavelet packet transform (DWPT) and the Itakura-Saito nonnegative matrix factorisation (ISNMF). In this approach, the speech signal was first split into a series of subband signals using the DWPT. Then, the ISNMF was used to enhance the speech for each subband signal. Finally, the inverse DWPT (IDWT) was utilised to reconstruct these enhanced speech subband signals. The experimental results show that the proposed joint framework effectively enhances the performance of speech enhancement and performs better in the unseen noise case compared to the traditional NMF methods.
Źródło:
Archives of Acoustics; 2020, 45, 4; 565-572
0137-5075
Pojawia się w:
Archives of Acoustics
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Regularized nonnegative matrix factorization: Geometrical interpretation and application to spectral unmixing
Autorzy:
Zdunek, R.
Powiązania:
https://bibliotekanauki.pl/articles/329732.pdf
Data publikacji:
2014
Wydawca:
Uniwersytet Zielonogórski. Oficyna Wydawnicza
Tematy:
blind source separation
nonnegative matrix factorization
active set algorithm
regularized NMF
polytope approximation
ślepa separacja sygnału
nieujemna faktoryzacja macierzy
Opis:
Nonnegative Matrix Factorization (NMF) is an important tool in data spectral analysis. However, when a mixing matrix or sources are not sufficiently sparse, NMF of an observation matrix is not unique. Many numerical optimization algorithms, which assure fast convergence for specific problems, may easily get stuck into unfavorable local minima of an objective function, resulting in very low performance. In this paper, we discuss the Tikhonov regularized version of the Fast Combinatorial NonNegative Least Squares (FC-NNLS) algorithm (proposed by Benthem and Keenan in 2004), where the regularization parameter starts from a large value and decreases gradually with iterations. A geometrical analysis and justification of this approach are presented. The numerical experiments, carried out for various benchmarks of spectral signals, demonstrate that this kind of regularization, when applied to the FC-NNLS algorithm, is essential to obtain good performance.
Źródło:
International Journal of Applied Mathematics and Computer Science; 2014, 24, 2; 233-247
1641-876X
2083-8492
Pojawia się w:
International Journal of Applied Mathematics and Computer Science
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Classification of Music Genres Based on Music Separation into Harmonic and Drum Components
Autorzy:
Rosner, A.
Schuller, B.
Kostek, B.
Powiązania:
https://bibliotekanauki.pl/articles/177566.pdf
Data publikacji:
2014
Wydawca:
Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:
music information retrieval
musical sound separation
drum separation
music genre classification
support vector machine (SVM)
co-training
nonnegative matrix factorization
Opis:
This article presents a study on music genre classification based on music separation into harmonic and drum components. For this purpose, audio signal separation is executed to extend the overall vector of parameters by new descriptors extracted from harmonic and/or drum music content. The study is performed using the ISMIS database of music files represented by vectors of parameters containing music features. The Support Vector Machine (SVM) classifier and co-training method adapted for the standard SVM are involved in genre classification. Also, some additional experiments are performed using reduced feature vectors, which improved the overall result. Finally, results and conclusions drawn from the study are presented, and suggestions for further work are outlined.
Źródło:
Archives of Acoustics; 2014, 39, 4; 629-638
0137-5075
Pojawia się w:
Archives of Acoustics
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Studying OpenMP thread mapping for parallel linear algebra kernels on multicore system
Autorzy:
Bylina, B.
Bylina, J.
Powiązania:
https://bibliotekanauki.pl/articles/200778.pdf
Data publikacji:
2018
Wydawca:
Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:
computation performance
OpenMP standard
nonnegative matrix factorization
thread mapping
energy consumption
wydajność obliczeniowa
Standard OpenMP
nieujemna faktoryzacja macierzy
mapowanie
zużycie energii
Opis:
Thread mapping is one of the techniques which allow for efficient exploiting of the potential of modern multicore architectures. The aim of this paper is to study the impact of thread mapping on the computing performance, the scalability, and the energy consumption for parallel dense linear algebra kernels on hierarchical shared memory multicore systems. We consider the basic application, namely a matrix-matrix product (GEMM), and two parallel matrix decompositions (LU and WZ). Both factorizations exploit parallel BLAS (basic linear algebra subprograms) operations, among others GEMM. We compare differences between various thread mapping strategies for these applications. Our results show that the choice of thread mapping has the measurable impact on the performance, the scalability, and energy consumption of the GEMM and two matrix factorizations.
Źródło:
Bulletin of the Polish Academy of Sciences. Technical Sciences; 2018, 66, 6; 981-990
0239-7528
Pojawia się w:
Bulletin of the Polish Academy of Sciences. Technical Sciences
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Rekonstrukcja niekompletnych obrazów za pomocą metod aproksymacji modelami niskiego rzędu
Image completion with low-rank model approximation methods
Autorzy:
Sadowski, T.
Zdunek, R.
Powiązania:
https://bibliotekanauki.pl/articles/408844.pdf
Data publikacji:
2017
Wydawca:
Politechnika Lubelska. Wydawnictwo Politechniki Lubelskiej
Tematy:
rekonstrukcja obrazów
aproksymacja niskiego rzędu
nieujemna faktoryzacja macierzy
dekompozycja tensorowa
uzupełnianie elementów macierzy
image completion
low-rank approximation
nonnegative matrix factorization
tensor decomposition
matrix completion
Opis:
W pracy badano zadanie rekonstrukcji brakujących pikseli w obrazach poddanych losowym zaburzeniom impulsowym w kanale transmisyjnym. Takie zadanie może być sformułowane w kontekście interpolacji obrazu na nieregularnej siatce lub aproksymacji niekompletnego obrazu za pomocą modeli dekompozycji obrazu na faktory niskiego rzędu. Porównano skuteczność czterech algorytmów opartych na dekompozycjach macierzy lub tensorów: SVT, SmNMF-MC, FCSA-TC i SPC-QV. Badania przeprowadzono na obrazach niekompletnych, otrzymanych z obrazów oryginalnych przez usunięcie losowo wybranych pikseli lub linii tworzących regularną siatkę. Najwyższą efektywność rekonstrukcji obrazu uzyskano gdy na estymowane faktory niskiego rzędu narzucano ograniczenia nieujemności i gładkości w postaci wagowej filtracji uśredniającej.
The paper is concerned with the task of reconstructing missing pixels in images perturbed with impulse noise in a transmission channel. Such a task can be formulated in the context of image interpolation on an irregular grid or by approximating an incomplete image by low-rank factor decomposition models. We compared four algorithms that are based on the low-rank decomposition model: SVT, SmNMF-MC , FCSA-TC and SPC-QV. The numerical experiments are carried out for various cases of incomplete images, obtained by removing random pixels or regular grid lines from test images. The best performance is obtained if nonnegativity and smoothing constraints are imposed onto the estimated low-rank factors.
Źródło:
Informatyka, Automatyka, Pomiary w Gospodarce i Ochronie Środowiska; 2017, 7, 4; 44-48
2083-0157
2391-6761
Pojawia się w:
Informatyka, Automatyka, Pomiary w Gospodarce i Ochronie Środowiska
Dostawca treści:
Biblioteka Nauki
Artykuł
Wyświetlanie 1-10 z 13

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