Informacja

Drogi użytkowniku, aplikacja do prawidłowego działania wymaga obsługi JavaScript. Proszę włącz obsługę JavaScript w Twojej przeglądarce.

Wyszukujesz frazę "nonnegative matrix" wg kryterium: Temat


Wyświetlanie 1-3 z 3
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:
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
    Wyświetlanie 1-3 z 3

    Ta witryna wykorzystuje pliki cookies do przechowywania informacji na Twoim komputerze. Pliki cookies stosujemy w celu świadczenia usług na najwyższym poziomie, w tym w sposób dostosowany do indywidualnych potrzeb. Korzystanie z witryny bez zmiany ustawień dotyczących cookies oznacza, że będą one zamieszczane w Twoim komputerze. W każdym momencie możesz dokonać zmiany ustawień dotyczących cookies