Gabor features has been recognized as one of the most successful representation methods, such as Elastic Graph Matching, Gabor Fisher Classifier, and AdaBoost Gabor Fisher Classifier. One of the key issues in using Gabor features is how to efficiently reduce its high dimensionality. This paper proposes a multiple Fisher classifiers combination approach based on re-grouping Gabor features select...

the study analyzed the information needs and accessibility of artisanal fisher folk in benue state, nigeria. multistage sampling technique was used to select two fishing communities from each of the three agro-ecological zones in the study area. a structured questionnaire was used to collect primary data from 222 respondents. descriptive statistics showed that artisanal fisher folk were mostly ...

in recent years, numerous approaches have been applied for finding the solutions of functional equations. one of them is the optimal homotopy asymptotic method. in current paper, this method has been applied for obtaining the approximate solution of fisher equation. the reliability of the method will be shown by solving some examples of various kinds and comparing the obtained outcomes with the ...

Only months from now, another decade will dawn on stroke research with a dearth of therapeutic innovations developed to reverse the devastating effects of acute ischemic stroke. Despite generations of academic research investigators and associated industry collaborations, our clinical trials have marked each decade by successive eras of failed treatments with only a few exceptions. The recent p...

Fisher Linear Discriminant Analysis (also called Linear Discriminant Analysis(LDA)) are methods used in statistics, pattern recognition and machine learning to find a linear combination of features which characterizes or separates two or more classes of objects or events. The resulting combination may be used as a linear classifier, or, more commonly, for dimensionality reduction before later c...

We show that it is possible to determine the locus of Fisher zeroes in the thermodynamic limit for the Ising model on planar (“fat”) φ random graphs and their dual quadrangulations by matching up the real part of the high and low temperature branches of the expression for the free energy. The form of this expression for the free energy also means that series expansion results for the zeroes may...

Fisher kernels provide a commonly used vectorial representation of structured objects. The paper presents a technique that exploits label information to improve the object representation of Fisher kernels by employing ideas from metric learning. In particular, the new technique trains a generative model in such a way that the distance between the log-likelihood gradients induced by two objects ...

At the present, several applications need to classify high dimensional points belonging to highly unbalanced classes. Unfortunately, when the training set cardinality is small compared to the data dimensionality (‘‘small sample size’’ problem) the classification performance of several well-known classifiers strongly decreases. Similarly, the classification accuracy of several discriminative met...

CCA can be seen as a multiview extension of PCA, in which information from two sources is used for learning by finding a subspace in which the two views are most correlated. However PCA, and by extension CCA, does not use label information. Fisher Discriminant Analysis uses label information to find informative projections, which can be more informative in supervised learning settings. We show ...