Intelligence Science and Big Data Engineering. Big Data and Machine Learning [electronic resource] : 9th International Conference, IScIDE 2019, Nanjing, China, October 17–20, 2019, Proceedings, Part II /

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Material type: Text

TextSeries: Image Processing, Computer Vision, Pattern Recognition, and Graphics ; 11936Publisher: Cham : Springer International Publishing : Imprint: Springer, 2019Edition: 1st ed. 2019Description: XX, 455 p. 357 illus., 145 illus. in color. online resourceContent type:

text

Media type:

computer

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online resource

ISBN:

9783030362041

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Additional physical formats: Printed edition:: No title; Printed edition:: No titleDDC classification:

006.37 23

LOC classification:

TA1634

Online resources:

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In: Springer Nature eBookSummary: The two volumes LNCS 11935 and 11936 constitute the proceedings of the 9th International Conference on Intelligence Science and Big Data Engineering, IScIDE 2019, held in Nanjing, China, in October 2019. The 84 full papers presented were carefully reviewed and selected from 252 submissions.The papers are organized in two parts: visual data engineering; and big data and machine learning. They cover a large range of topics including information theoretic and Bayesian approaches, probabilistic graphical models, big data analysis, neural networks and neuro-informatics, bioinformatics, computational biology and brain-computer interfaces, as well as advances in fundamental pattern recognition techniques relevant to image processing, computer vision and machine learning. .

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The two volumes LNCS 11935 and 11936 constitute the proceedings of the 9th International Conference on Intelligence Science and Big Data Engineering, IScIDE 2019, held in Nanjing, China, in October 2019. The 84 full papers presented were carefully reviewed and selected from 252 submissions.The papers are organized in two parts: visual data engineering; and big data and machine learning. They cover a large range of topics including information theoretic and Bayesian approaches, probabilistic graphical models, big data analysis, neural networks and neuro-informatics, bioinformatics, computational biology and brain-computer interfaces, as well as advances in fundamental pattern recognition techniques relevant to image processing, computer vision and machine learning. .

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