Soft Computing in Image Processing: Recent Advances

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Submissions must be original and should not have been published previously or be under consideration for publication while being evaluated for this conference.

Michael Elad: "Sparse Modeling in Image Processing and Deep Learning"

Selected papers from SAI , after further revisions, will be published in the special issues of the following journals. Mikhail Khlebnikov V. Hard copy of the proceedings will be distributed during the Conference.


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Authors are solicited to contribute to the conference by submitting articles that illustrate research results, projects, surveying works and industrial experiences that describe significant advances in the following areas, but are not limited to. Architects International.

دریافت: Soft Computing in Image Processing: Recent Advances |ایی ایی

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Shodh International. Fuzzy Logic: It is based on the observation that people make decisions based on imprecise and non-numerical information. These models have the capability of recognizing, representing, manipulating, interpreting, and utilizing data and information that are vague and lack certainty 2. Evolutionary Computation: It is a family of algorithms for global optimization inspired by biological evolution. Evolutionary computation techniques can produce highly optimized solutions in a wide range of problem settings.

Machine Learning: Machine learning algorithms are used in a wide variety of applications, such as big data analysis, and image processing, where it is infeasible to develop an algorithm of specific instructions for performing the task.


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Machine learning is closely related to computational statistics, which focuses on making predictions using computers. Probabilistic Reasoning: The aim of a probabilistic logic is to combine the capacity of probability theory to handle uncertainty with the capacity of deductive logic to exploit the structure of formal argument.

Recent Advances

Probabilistic logics attempt to find a natural extension of traditional logic truth tables: the results they define are derived through probabilistic expressions instead. Generally, soft computing techniques resemble biological processes more closely than traditional techniques, which are largely based on formal logical systems, such as sentential logic and predicate logic, or rely heavily on computer-aided numerical analysis.

Soft Computing in Image Processing: Recent Advances (Studies in Fuzziness and Soft Computing)

Soft computing techniques are intended to complement each other. This special issue is aimed towards innovative research works in all the categories of soft computing, such as Fuzzy Logic, Evolutionary Computation, Machine Learning and Probabilistic Reasoning along with new strategies for information analysis and architectures:.

Evolutionary Computation Systems: 1.

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