No abstract

In this paper, face authentication using images taken in visible and near-infrared spectra (NIR) is studied. Visible images are in RGB colour space and near-infrared images are in gray levels colour space. First, the performance of system in each of the primary colour spaces of visible and near-infrared spectrum is evaluated that the verification process is based on the Normalised Correlation measure within the LDA feature space. In order to utilize the information of colour images, the scores associated to an adaptively selected subset of the colour based classifiers are then fused in the decision level. The selection process is based on a sequential search technique called the"plus L and take away R" algorithm. The sum rule and svm rule is used for fusing the related scores. Our extensive experimental studies using the HFB face database demonstrate that using the proposed method, the performance of the system considerably improves as compared to the individual Visible-based or NIR-based face verification systems.

With the advent of microarray technology it has been possible to measure thousands of expression values of genes in a single experiment. Analysis of large scale geonomics data, notably gene expression, has initially focused on clustering methods. Recently, biclustering techniques were proposed for revealing submatrices showing unique patterns. Biclustering or simultaneous clustering of both genes and conditions is challenging particularly for the analysis of high-dimensional gene expression data in information retrieval, knowledge discovery, and data mining. In biclustering of microarray data, several objectives have to be optimized simultaneously and often these objectives are in conflict with each other. A multi objective model is very suitable for solving this problem. Our method proposes a algorithm which is based on multi objective Simulated Annealing for discovering biclusters in gene expression data. Experimental result in bench mark data base present a significant improvement in overlap among biclusters and coverage of elements in gene expression and quality of biclusters.