Evaluation of distance metrics for recognition based on non-negative matrix factorization
Pattern Recognition Letters
Learning Image Components for Object Recognition
The Journal of Machine Learning Research
Nonnegative matrix factorization with quadratic programming
Neurocomputing
Non-negative matrix factorisation for object class discovery and image auto-annotation
CIVR '08 Proceedings of the 2008 international conference on Content-based image and video retrieval
Blind Image Separation Using Nonnegative Matrix Factorization with Gibbs Smoothing
Neural Information Processing
Data Clustering with Semi-binary Nonnegative Matrix Factorization
ICAISC '08 Proceedings of the 9th international conference on Artificial Intelligence and Soft Computing
Computational Intelligence and Neuroscience - Advances in Nonnegative Matrix and Tensor Factorization
Face Image Recognition Combining Holistic and Local Features
ISNN 2009 Proceedings of the 6th International Symposium on Neural Networks: Advances in Neural Networks - Part III
Unsupervised learning of overlapping image components using divisive input modulation
Computational Intelligence and Neuroscience
Non-negative matrix factorization on Kernels
PRICAI'06 Proceedings of the 9th Pacific Rim international conference on Artificial intelligence
Robust automatic data decomposition using a modified sparse NMF
MIRAGE'07 Proceedings of the 3rd international conference on Computer vision/computer graphics collaboration techniques
Nonnegative Matrix Factorization on Orthogonal Subspace
Pattern Recognition Letters
A new feature extraction and selection scheme for hybrid fault diagnosis of gearbox
Expert Systems with Applications: An International Journal
Class-specific discriminant non-negative matrix factorization for frontal face verification
ICAPR'05 Proceedings of the Third international conference on Pattern Recognition and Image Analysis - Volume Part II
Two-dimensional non-negative matrix factorization for face representation and recognition
AMFG'05 Proceedings of the Second international conference on Analysis and Modelling of Faces and Gestures
Non-monotone projection gradient method for non-negative matrix factorization
Computational Optimization and Applications
Review article: Max-margin Non-negative Matrix Factorization
Image and Vision Computing
Nonnegative matrix factorizations performing object detection and localization
Applied Computational Intelligence and Soft Computing
Solving non-negative matrix factorization by alternating least squares with a modified strategy
Data Mining and Knowledge Discovery
Spatially correlated nonnegative matrix factorization for image analysis
IScIDE'12 Proceedings of the third Sino-foreign-interchange conference on Intelligent Science and Intelligent Data Engineering
Modified subspace Barzilai-Borwein gradient method for non-negative matrix factorization
Computational Optimization and Applications
Discriminant Convex Non-negative Matrix Factorization for the classification of human brain tumours
Pattern Recognition Letters
| Hi-index | 0.10 |
Non-negative matrix factorization (NMF) is a new feature extraction method. But the learned feature vectors are not directly suitable for further analysis such as object recognition using the nearest neighbor classifier in contrast to traditional principal component analysis (PCA) because the learned bases are not orthonormal to each other. This paper investigates how to improve the accuracy of recognition based on this new method from two viewpoints. One is to adopt a Riemannian metric like distance for the learned feature vectors instead of Euclidean distance. The other is to first orthonormalize the learned bases and then to use the projections of data based on the orthonormalized bases for further recognition. Experiments on the USPS database demonstrate the proposed methods can improve accuracy and even outperform PCA. We believe that the proposed methods can make NMF used as widely as PCA.