The methods involve dynamic and global features, using spectral, fundamental frequency, and temporal information.
Later, to improve the high-dimensional feature selection, Liu et al. [6] attempt to learn discriminative high-dimensional features using dynamic sparsity group.
This paper presents a generalized framework for segmenting closed-contour anatomical and pathological features using graph theory and dynamic programming (GTDP).
The features retained by the selection procedure (area, eccentricity, compactness, and perimeter as morphological features; and SOD, basal signal, and relative enhancement slope as dynamic features) were used to assess the performance of the single classifier and of the MCS.
With MCS implementation, an increase in accuracy of 12.5% and of 31.3% was obtained when comparing the Bayesian classifier using dynamic features with the decision tree using morphological features, respectively.
The algorithm has 23.29% improvements of the relative error rate in comparison with the standard MFCC feature-set and the dynamic features in tests using THEESP with the duration distribution-based hidden Markov model (DDBHMM) based on MASR system.
This makes resolving any short-term variability in dynamic features difficult when using satellite observations alone (Forbes et al. 1997).
Our prime focus is not to achieve lowest error rate for used data set mnist but to propose a technique with hybrid features where static and dynamic features could be used together.
In this section, the spatiotemporal features used for the representation of dynamic texture patches are defined.
In [10], we used multiple acoustic frames (MAF) as an acoustic dynamic feature to improve the recognition rate of a person with an articulation disorder, especially in speech recognition using dynamic features only.
