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Recently, two-dimensional canonical correlation analysis (2DCCA) has been successfully applied for image feature extraction. The method instead of concatenating the columns of the images to the one-dimensional vectors, directly works with two-dimensional image matrices. Although 2DCCA works well in different recognition tasks, it lacks a probabilistic interpretation. In this paper, we present a probabilistic...
A main goal of data visualization is to find, from among all the available alternatives, mappings to the 2D/3D display which are relevant to the user. Assuming user interaction data, or other auxiliary data about the items or their relationships, the goal is to identify which aspects in the primary data support the user's input and, equally importantly, which aspects of the user's potentially noisy...
Least squares twin support vector machine (LSTSVM) is a relatively new version of support vector machine (SVM) based on non-parallel twin hyperplanes. Although, LSTSVM is an extremely efficient and fast algorithm for binary classification, its parameters depend on the nature of the problem. Problem dependent parameters make the process of tuning the algorithm with best values for parameters very difficult,...
Recently, two-dimensional canonical correlation analysis (2DCCA) proved to be an efficient technique for image feature extraction. In this paper we present a method of 2DCCA with probabilistic framework called probabilistic 2DCCA (P2DCCA), which is robust to noise and is able to cope with missing data problems. The experimental recognition results on three subsets of AR face database show the robustness...
Difficulties of tackling real-world problems with their growing complexities motivated computer scientists to search for more efficient problem solving approaches. Metaheuristic algorithms are outstanding examples of these ap-proaches. Bat Algorithm (BA) is a new meta-heuristic optimization algorithm, which has been developed rapidly and has been applied in different optimization tasks in recent years...
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