Post Description

█ Quantum-Inspired Soft Computing for Binary Image Analysis               
    █                                                              
    ▄
    █ by Siddhartha Bhattacharyya                                     
    █ Publisher: IGI Global                                           
    ▓ Release Date: May 2016                                          
    ▒ ISBN: 9781522507680                                             
    ▒ Running time: 1:16:43                                           
    ░ Topic: Engineering                                              
    ░ Size: 08x50mb         

    ░ Course Description: Several classical techniques have evolved over the  
                          years for the purpose of de-noising binary images as 
                          a part of image enhancement. Filtering techniques 
                          remain at the helm as different filters can be 
                          designed to cater to various noisy characteristics. 
                          The main disadvantages of these classical techniques 
                          lie in that an a priori information regarding the 
                          noise characteristics is required during the 
                          extraction process. Among the intelligent techniques 
                          in vogue, the multilayer self-organizing neural 
                          network (MLSONN) architecture is suitable for binary 
                          image preprocessing tasks. Quantum-Inspired Soft 
                          Computing for Binary Image Analysis introduces a 
                          quantum version of the MLSONN architecture. Similar 
                          to the MLSONN architecture, the proposed quantum 
                          multilayer self-organizing neural network (QMLSONN) 
                          architecture comprises three processing layers viz., 
                          input, hidden and output layers. This video lecture 
                          is an innovative resource for practitioners, 
                          researchers, and graduate-level students interested 
                          in learning about emerging computer vision 
                          techniques.

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