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Titlebook: Smart Intelligent Computing and Applications; Proceedings of the T Suresh Chandra Satapathy,Vikrant Bhateja,Siba K. U Conference proceeding

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书目名称Smart Intelligent Computing and Applications
副标题Proceedings of the T
编辑Suresh Chandra Satapathy,Vikrant Bhateja,Siba K. U
视频video
概述Presents cutting-edge research papers on the design of smart computing and information systems.Focuses on various innovation paradigms in system knowledge, intelligence, and sustainability.Covers nove
丛书名称Smart Innovation, Systems and Technologies
图书封面Titlebook: Smart Intelligent Computing and Applications; Proceedings of the T Suresh Chandra Satapathy,Vikrant Bhateja,Siba K. U Conference proceeding
描述.This book gathers high-quality papers presented at the Third International Conference on Smart Computing and Informatics (SCI 2018–19), which was organized by the School of Computer Engineering and School of Computer Application, Kalinga Institute of Industrial Technology, Bhubaneswar, India, on 21–22 December, 2018. It includes advanced and multi-disciplinary research on the design of smart computing and informatics. Thematically, the book broadly focuses on several innovation paradigms in system knowledge, intelligence and sustainability that can help to provide realistic solutions to various problems confronting society, the environment, and industry. The respective papers offer valuable insights into the how emerging computational and knowledge transfer approaches can be used to deliver optimal solutions in science, technology and healthcare..
出版日期Conference proceedings 2020
关键词SCI 2018-2019; Data Analytics; Data Base Management; ICT for Education; Big Data; Optical Computing; Cloud
版次1
doihttps://doi.org/10.1007/978-981-13-9282-5
isbn_softcover978-981-13-9284-9
isbn_ebook978-981-13-9282-5Series ISSN 2190-3018 Series E-ISSN 2190-3026
issn_series 2190-3018
copyrightSpringer Nature Singapore Pte Ltd. 2020
The information of publication is updating

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Mango Leaves Recognition Using Deep Belief Network with Moth-Flame Optimization and Multi-feature Fion (MFO)-based deep belief network (DBN) method for plant leaf recognition. Initially, a combination of texture and shape features is applied for extracting features from preprocessed image. Further, for leaf classification, the MFO optimizes the DBN parameters to minimize error and is used as clas
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