Random Subspace Method (RSM): Properties and Applications
Covariate invariant gait recognition using random subspace method and its extensions
... applications, the results in Fig.3.4 suggest that when the running gallery is unavailable, a faster walking gallery is more suitable for runner identification. 3.3.4 Discussion For the fixed-mode gait recognition, ...
162
Random subspace method for aource camera identification
... proposed method has the capability to suppress the interference of scene details and achieves a superior ROC curve performance than both the original SPN extraction method and the PCA-based feature ...
6
A Novel Random Subspace Method for Online Writeprint Identification
... two-stage method of PCA+LDA is used to reduce feature ...PCA subspace depends on the size of training set, which avoids classifier over-fitting ...PCA subspace using proposed RSM, we apply LDA for ...
8
Random Trees and Applications ∗
... 3. The Brownian Snake and its Connections with Partial Differential Equations Our goal in this section is to combine the continuous tree structure studied in the previous section with independent spatial motions: In ...
67
Random Subspace Learning on Outlier Detection and Classification with Minimum Covariance Determinant Estimator
... One of the benefits of RSM for building and aggregating the classifiers is the num- ber of dimensionality may be much smaller than the original data. In sub-feature spaces the sample size does not change. So this ...
95
Random ultrametric trees and applications*
... In this paper, we review some mathematical properties of random tree models bearing in mind potential applications to evolutionary biology. Trees are used in population genetics, to trace the ...
20
A model and architecture for pseudo-random generation with applications to /dev/random
... In this work we formalize the requirements that we believe are needed from a robust pseudoran- dom generator, and describe an architecture to realize these properties. Underlying our model is the view that ...
20
Evolutionary Weights for Random Subspace Learning
... With the method on how the weights are updated, we could speculate on what will happen as the size of the ensemble grows. The first thing that comes to mind, is that this scheme will begin to give higher weights ...
67
Applications of Optimal Subspace Estimation
... the subspace when a poorly calibrated array is introduced because the resulting signal matrix no longer has the structure the al- gorithm relies ...better method. Some applications may require a ...
67
An Adaptive Constraint Method for Paraunitary Filter Banks with Applications to Spatiotemporal Subspace Tracking
... tive method, we analyze the dynamics of our proposed it- erative procedure, showing that convergence of the method is locally ...spatiotemporal subspace track- ing algorithms, the method is ...
11
Random subspace ensembles for the bio-molecular diagnosis of tumors.
... the random subspace ensembles of linear SVMs have revealed the effectiveness of the approach with colon and medulloblastoma data ...the random subspace ensemble approach with feature selection ...
12
Random Subspace Learning Approach to High Dimensional Outliers Detection
... detection method for both HDLSS and LDHSS ...both random subspace learning and minimum covariance determinant, our proposed approach can be readily used on vast number of real life examples where ...
13
Manifold-enhanced Segmentation through Random Walks on Linear Subspace Priors
... LINEAR SUBSPACE PRIORS AND RANDOM WALKS SEGMENTATION target image in an initial state and deformed by minimizing an objective function composed of two terms: a data-term - attracting the surface to detected ...
11
Approximate Nearest Subspace Search with Applications to Pattern Recognition
... a subspace near to the ...nearest subspace problem for both lin- ear and affine subspaces. Our method is based on a simple reduction to the problem of nearest point search, and can thus employ tree ...
8
Improve the Active Subspace Method by Partitioning the Parameter Space
... The original active subspace works on models that have a ridge struc- ture. In other words, one can find a set of directions where the function values vary only along these directions. However, models may not ...
98
Two-subspace Projection Method for Coherent Overdetermined Systems
... many applications such as nonuniform sampling in Fourier analysis, as discussed in Section ...two-subspace method still guarantees substantial improvement over the standard ...
20
An Advance Subspace Method For Implementing Palm Print Recognition
... by random orientations of tissues and muscles of the hand during birth, no two individuals have exactly the same palm print ...civil applications such as financial transaction, access control, ...forensic ...
5
Review on Speech Enhancement using Signal Subspace method
... Speech is most natural form of human communication. The perception of speech signal is usually measured in terms of its quality and intelligibility. The quality is a subjective measures that indicates the pleasantness or ...
7
Action Recognition Framework using Saliency Detection and Random Subspace Ensemble Classifier
... neighboring method was used to display the observed orbit from automated overlaps arising from the projection of dynamically dynamic systems to lower dimension space ...
9
A subspace recursive and selective feature transformation method for classification tasks
... non-linear Random Forest Classifier RST, along with other two feature transformers even deteriorates the classification ...since Random Forest’s feature extraction techniques is to use multiple ...
10