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This paper addresses one of the primary problems of visual information processing known as image restoration. Image restoration is a challenging task because of its ill-posed inverse nature. A modified Hopfield neural network with fuzzy adaptive regularization is proposed that shows potential to minimize constraint mean square error in order to guarantee the optimized results. Adaptive regularization...
In recent times, the applications of image processing have grown immensely. Usually due to limited depth of field of optical lenses especially with greater focal length, it becomes impossible to obtain an image where all the objects are in focus. Image fusion deals with creating an image in which all the objects are in focus. Thus it plays an important role to perform other tasks of image processing...
In protein fold recognition problem an effort is made to assign a fold to given proteins, this is of practical importance and has diverse application in the field of bioinformatics such as the discovery of new drugs, the individual implication of amino acid in a protein and bringing improvement in a specific protein function. In this paper, we have studied various machine learning techniques for protein...
In this paper, a novel lattice constant prediction model based on support vector machine is proposed. In this proposed technique, advanced data set generation technique is also used which is helpful to develop fairly generalized prediction models. This enables us to achieve improved prediction performance of lattice constant of structurally known perovskites. Experimental results obtained using orthorhombic...
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