• Title/Summary/Keyword: NMF

Search Result 157, Processing Time 0.025 seconds

Dimension-Reduced Audio Spectrum Projection Features for Classifying Video Sound Clips

  • Kim, Hyoung-Gook
    • The Journal of the Acoustical Society of Korea
    • /
    • v.25 no.3E
    • /
    • pp.89-94
    • /
    • 2006
  • For audio indexing and targeted search of specific audio or corresponding visual contents, the MPEG-7 standard has adopted a sound classification framework, in which dimension-reduced Audio Spectrum Projection (ASP) features are used to train continuous hidden Markov models (HMMs) for classification of various sounds. The MPEG-7 employs Principal Component Analysis (PCA) or Independent Component Analysis (ICA) for the dimensional reduction. Other well-established techniques include Non-negative Matrix Factorization (NMF), Linear Discriminant Analysis (LDA) and Discrete Cosine Transformation (DCT). In this paper we compare the performance of different dimensional reduction methods with Gaussian mixture models (GMMs) and HMMs in the classifying video sound clips.

Vehicle Face Recognition Algorithm Based on Weighted Nonnegative Matrix Factorization with Double Regularization Terms

  • Shi, Chunhe;Wu, Chengdong
    • KSII Transactions on Internet and Information Systems (TIIS)
    • /
    • v.14 no.5
    • /
    • pp.2171-2185
    • /
    • 2020
  • In order to judge that whether the vehicles in different images which are captured by surveillance cameras represent the same vehicle or not, we proposed a novel vehicle face recognition algorithm based on improved Nonnegative Matrix Factorization (NMF), different from traditional vehicle recognition algorithms, there are fewer effective features in vehicle face image than in whole vehicle image in general, which brings certain difficulty to recognition. The innovations mainly include the following two aspects: 1) we proposed a novel idea that the vehicle type can be determined by a few key regions of the vehicle face such as logo, grille and so on; 2) Through adding weight, sparseness and classification property constraints to the NMF model, we can acquire the effective feature bases that represent the key regions of vehicle face image. Experimental results show that the proposed algorithm not only achieve a high correct recognition rate, but also has a strong robustness to some non-cooperative factors such as illumination variation.

Document Clustering using Non-negative Matrix Factorization and Fuzzy Relationship (비음수 행렬 분해와 퍼지 관계를 이용한 문서군집)

  • Park, Sun;Kim, Kyung-Jun
    • Journal of Advanced Navigation Technology
    • /
    • v.14 no.2
    • /
    • pp.239-246
    • /
    • 2010
  • This paper proposes a new document clustering method using NMF and fuzzy relationship. The proposed method can improve the quality of document clustering because the clustered documents by using fuzzy relation values between semantic features and terms to distinguish well dissimilar documents in clusters, the selected cluster label terms by using semantic features with NMF, which is used in document clustering, can represent an inherent structure of document set better. The experimental results demonstrate that the proposed method achieves better performance than other document clustering methods.

Query-Based Summarization using Non-negative Matrix Factorization (비음수 행렬 인수분해를 이용한 질의 기반의 문서 요약)

  • Park Sun;Lee Ju-Hong;Ahn Chan-Min;Park Tae-Su;Kim Deok-Hwan
    • Proceedings of the Korean Information Science Society Conference
    • /
    • 2006.06a
    • /
    • pp.394-396
    • /
    • 2006
  • 기존 질의기반의 문서요약은 질의와 문서간의 사전 학습으로 요약의 질을 높이거나, 문서의 고유 구조(inherent structure)를 반영하여 요약의 정확도를 높이기 위하여 문서를 그래프로 변환한다. 본 논문은 비음수 행렬 인수분해 (NMF, Non-negative Matrix Factorization)를 이용하여 질의 기반의 문서를 요약하는 새로운 방법을 제안하였다. 제안된 방법은 질의와 문서간에 사전학습이 필요 없다. 또한 문서를 그래프로 변형시키는 복잡한 처리 없이 NMF에 의해 얻어진 의미 특징(semantic feature)과 의미 변수(semantic variable)로 문서의 고유 구조를 반영하여 요약의 정확도를 높일 수 있다. 마지막으로 단순한 방법으로 문장을 쉽게 요약 할 수 있다.

  • PDF

Nonnegative Tucker Decomposition (텐서의 비음수 Tucker 분해)

  • Kim, Yong-Deok;Choi, Seung-Jin
    • Journal of KIISE:Computing Practices and Letters
    • /
    • v.14 no.3
    • /
    • pp.296-300
    • /
    • 2008
  • Nonnegative tensor factorization(NTF) is a recent multiway(multilineal) extension of nonnegative matrix factorization(NMF), where nonnegativity constraints are imposed on the CANDECOMP/PARAFAC model. In this paper we consider the Tucker model with nonnegativity constraints and develop a new tensor factorization method, referred to as nonnegative Tucker decomposition (NTD). We derive multiplicative updating algorithms for various discrepancy measures: least square error function, I-divergence, and $\alpha$-divergence.

Enhancing Text Document Clustering Using Non-negative Matrix Factorization and WordNet

  • Kim, Chul-Won;Park, Sun
    • Journal of information and communication convergence engineering
    • /
    • v.11 no.4
    • /
    • pp.241-246
    • /
    • 2013
  • A classic document clustering technique may incorrectly classify documents into different clusters when documents that should belong to the same cluster do not have any shared terms. Recently, to overcome this problem, internal and external knowledge-based approaches have been used for text document clustering. However, the clustering results of these approaches are influenced by the inherent structure and the topical composition of the documents. Further, the organization of knowledge into an ontology is expensive. In this paper, we propose a new enhanced text document clustering method using non-negative matrix factorization (NMF) and WordNet. The semantic terms extracted as cluster labels by NMF can represent the inherent structure of a document cluster well. The proposed method can also improve the quality of document clustering that uses cluster labels and term weights based on term mutual information of WordNet. The experimental results demonstrate that the proposed method achieves better performance than the other text clustering methods.

여름철 그을린 피부손질

  • Kim, Gi-Yeon
    • 건강소식
    • /
    • v.9 no.8 s.81
    • /
    • pp.46-49
    • /
    • 1985
  • 불타는 태양은 우리와 함께하고 여름의 낭만이 우리를 손짓하지만 여름의 낭만이 우리를 손짓하지만 여름을 맞이한 피부는 높은 기온과 강한 자외선으로 피지 분비가 많아지고 피부내 자연보습성분인 NMF와 수분이 감소되어, 피부는 거칠어 집니다.

  • PDF

Automatic Email Multi-category Classification Using Dynamic Category Hierarchy and Non-negative Matrix Factorization (비음수 행렬 분해와 동적 분류 체계를 사용한 자동 이메일 다원 분류)

  • Park, Sun;An, Dong-Un
    • Journal of KIISE:Software and Applications
    • /
    • v.37 no.5
    • /
    • pp.378-385
    • /
    • 2010
  • The explosive increase in the use of email has made to need email classification efficiently and accurately. Current work on the email classification method have mainly been focused on a binary classification that filters out spam-mails. This methods are based on Support Vector Machines, Bayesian classifiers, rule-based classifiers. Such supervised methods, in the sense that the user is required to manually describe the rules and keyword list that is used to recognize the relevant email. Other unsupervised method using clustering techniques for the multi-category classification is created a category labels from a set of incoming messages. In this paper, we propose a new automatic email multi-category classification method using NMF for automatic category label construction method and dynamic category hierarchy method for the reorganization of email messages in the category labels. The proposed method in this paper, a large number of emails are managed efficiently by classifying multi-category email automatically, email messages in their category are reorganized for enhancing accuracy whenever users want to classify all their email messages.

Study on the Relationship between Skin Dryness and Amino Acids in Stratum Corneum (아미노산 동시분석을 통한 피부보습능과 각질 중 아미노산 함량과의 상관관계 연구)

  • Joo, Kyung-Mi;Han, Ji-Yeon;Son, Eui-Dong;Nam, Gae-Won;Jeong, Hye-Jin;Lim, Kyung-Min;Cho, Jun-Cheol
    • Journal of the Society of Cosmetic Scientists of Korea
    • /
    • v.38 no.1
    • /
    • pp.75-82
    • /
    • 2012
  • Natural moisturizing factors (NMFs) are hydrophilic and water-soluble components in stratum corneum of the skin. NMFs absorb water from outer environment and enhance the water-holding capacity of stratum corneum and thereby, prevent the dryness and increase flexibility and plasticity of skin. NMFs are mainly composed of amino acids and their metabolites that are produced from the degradation of filaggrin. Here we established a simultaneous quantification method for 22 amino acids in tape-stripped stratum corneum samples using UPLC-PDA. With this method, we analyzed amino acid contents from tape-stripped stratum corneum samples of forearm and forehead regions from 15 healthy volunteers. Amino acid contents of inner (or upper) region were higher than outer (or lower) region of stratum corneum. Amino acid contents of stratum corneum of forearm were higher by 1.5 fold than forehead region. Of note, total amino acid contents were significantly and inversely correlated with trans-epidermal water loss (TEWL), an index for skin barrier function. Especially, Ser, Glu, Gly, Ala and Thr were determined to positively affect skin mositurizing activities. In conclusion, we could demonstrate that amino acid contents of stratum corneum are closely linked with skin barrier and moisturizing function, providing an important and fundamental methodology for the study of amino acids in skin physiology.

CONVERGENCE ANALYSIS OF THE EAPG ALGORITHM FOR NON-NEGATIVE MATRIX FACTORIZATION

  • Yang, Chenxue;Ye, Mao
    • Journal of applied mathematics & informatics
    • /
    • v.30 no.3_4
    • /
    • pp.365-380
    • /
    • 2012
  • Non-negative matrix factorization (NMF) is a very efficient method to explain the relationship between functions for finding basis information of multivariate nonnegative data. The multiplicative update (MU) algorithm is a popular approach to solve the NMF problem, but it fails to approach a stationary point and has inner iteration and zero divisor. So the elementwisely alternating projected gradient (eAPG) algorithm was proposed to overcome the defects. In this paper, we use the fact that the equilibrium point is stable to prove the convergence of the eAPG algorithm. By using a classic model, the equilibrium point is obtained and the invariant sets are constructed to guarantee the integrity of the stability. Finally, the convergence conditions of the eAPG algorithm are obtained, which can accelerate the convergence. In addition, the conditions, which satisfy that the non-zero equilibrium point exists and is stable, can cause that the algorithm converges to different values. Both of them are confirmed in the experiments. And we give the mathematical proof that the eAPG algorithm can reach the appointed precision at the least iterations compared to the MU algorithm. Thus, we theoretically illustrate the advantages of the eAPG algorithm.