Email plays a vital role in faster communication. Lots of mails are sent to common public with falsified information that appears to be a realistic. It is mandatory to trace the origin of the email and the authors/systems responsible for generating such emails. Representative signatures of email are to be generated using lexical and syntactic based methods. The signature of each email has huge ...

In this paper, a face recognition algorithm using multi feature and Radial basis Function Network (RBFN) is proposed. The algorithm consists of three steps. In the first step, a coarse classification is performed using Fourier frequency spectrum feature, and only the first k gallery images with minimum Euclidean distance to the probe image are retained. In the second step, the Principal Compone...

We analyze the capabilities of CASI data for the discrimination of vine varieties in hyperspectral images. To analyze the discrimination capabilities of the CASI data, principal components analysis and linear discriminant analysis methods are used. We assess the performance of various classification techniques: Multi-layer perceptrons, radial basis function neural networks, and support vector m...

The likelihood approach used in this paper leads to quadratic discriminant functions. Classification into one of two known multivariate normal populations with a and unknown covariance matrix are separately considered, where the cases depend on sample size an squared Mahalanobis distance. Their exact distributions complicated obtain. Therefore, moments for based functions established express ba...

In this article, we address the problem of thistle detection in sugar beet fields under natural, outdoor conditions. In our experiments, we used a commercial color camera and extracted vegetation indices from the images. A total of 474 field images of sugar beet and thistles were collected and divided into six different groups based on illumination, scale and age. The feature set was made up of...

Liquid State Machines constitute a powerful computational tool for carrying out complex real time computations on continuous input streams. Their performance is based on two properties, approximation and separation. While the former depends on the selection of class functions for the readout maps, the latter needs to be evaluated for a particular liquid architecture. In the current paper we sho...

Gene selection aims at identifying a (small) subset of informative genes from the initial data in order to obtain high predictive accuracy. This paper introduces a new wrapper approach to this difficult task where a Genetic Algorithm (GA) is combined with Fisher’s Linear Discriminant Analysis (LDA). This LDA-based GA algorithm has the major characteristic that the GA uses not only a LDA classif...

We explore a method to boost discriminative capabilities of Probabilistic Linear Discriminant Analysis (PLDA) model without losing its generative advantages. To this end, our focus is in a low-dimensional PLDA latent subspace. We optimize the model with respect to MMI (Maximum Mutual Information) and our own objective functions, which is an approximation to the detection cost function. We evalu...

Probabilistic Linear Discriminant Analysis (PLDA) has become state-of-the-art method for modeling i-vector space in speaker recognition task. However the performance degradation is observed if enrollment data size differs from one speaker to another. This paper presents a solution to such problem by introducing new PLDA scoring normalization technique. Normalization parameters are derived in a ...