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Titlebook: Soft Computing Techniques in Engineering Applications; Srikanta Patnaik,Baojiang Zhong Book 2014 Springer International Publishing Switzer

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Medical Image Analysis Using Soft Computing Techniques,valuation of medical data. The processing of medical data includes two major processes called as segmentation and classification. Image segmentation is the process in which a single image is partitioned into several groups based on similarity measures. Image classification is the process in which se
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Numerical Study of Viscous Flow in the Hydraulic System of Electro Optical Tracking System,us and incompressible fluid flow in rectangular pipe. The numerical results have been corroborated through a scaling law and asymptotic analysis. It deals with simulation of viscous flow in a typical hydraulic control system can be used in Electro Optical Tracking System (EOTS). Due to geometric con
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Comparison of Edge Detection Algorithm for Part Identification in a Vision Guided Robotic Assembly nt tasks which need to be carefully done by a vision system to initiate the process. This process consists of many sub-processes wherein, the image capturing, digitizing and enhancing, etc. do account for reconstructive the part for subsequent operations. Edge detection of the grabbed image, therefo
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1860-949X nitive Psychology, and Psychophysics.Written by experts in t.The Soft Computing techniques, which are based on the information processing of biological systems are now massively used in the area of pattern recognition, making prediction & planning, as well as acting on the environment. Ideally speak
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Comparison of Edge Detection Algorithm for Part Identification in a Vision Guided Robotic Assembly on the Matlab R2012a Simulink. The algorithm considered here are Canny’s, Robert, Perwitt, Sobel, and LOG edge detection algorithms. An attempt has been made to find the best algorithm for the problem. It is found that Canny’s edge detection algorithm gives better result with negligible error for the intended task.
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Multi Objective Line Symmetry Based Evolutionary Clustering Approach,points. Experimental results based on several artificial data sets show that proposed multi objective genetic clustering can obtain optimal clustering solutions in terms of different cluster quality measures and classification performance with compared to existing clustering algorithm SBKM.
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