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Machine learning approaches for urba...

Bandyopadhyay, Mainak.

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Machine learning approaches for urban computing

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Machine learning approaches for urban computing/ edited by Mainak Bandyopadhyay, Minakhi Rout, Suresh Chandra Satapathy.
其他作者:	Bandyopadhyay, Mainak.
出版者:	Singapore :Springer Singapore : : 2021.,
面頁冊數:	xi, 208 p. :ill. (some col.), digital ;24 cm.
內容註:	Urbanization: Pattern, Effects and Modelling -- Extraction of Information from Hyperspectral Imaging using Deep Learning -- Vehicle Detection and count in the captured Stream Video using Machine Learning -- Dimensionality Reduction and Classification in Hyperspectral Images using Deep Learning -- Machine learning and deep learning algorithms in the diagnosis of chronic diseases -- Security Enhancement of Contact less Tachometer Based Cyber Physical System -- Optimization of Loss Function on Human Faces Using Generative Adversarial Networks.
Contained By:	Springer Nature eBook
標題:	Smart cities. -
電子資源:	https://doi.org/10.1007/978-981-16-0935-0
ISBN:	9789811609350

Machine learning approaches for urban computing
Machine learning approaches for urban computing[electronic resource] /edited by Mainak Bandyopadhyay, Minakhi Rout, Suresh Chandra Satapathy. - Singapore :Springer Singapore :2021. - xi, 208 p. :ill. (some col.), digital ;24 cm. - Studies in computational intelligence,v.9681860-949X ;. - Studies in computational intelligence ;v.968..

Urbanization: Pattern, Effects and Modelling -- Extraction of Information from Hyperspectral Imaging using Deep Learning -- Vehicle Detection and count in the captured Stream Video using Machine Learning -- Dimensionality Reduction and Classification in Hyperspectral Images using Deep Learning -- Machine learning and deep learning algorithms in the diagnosis of chronic diseases -- Security Enhancement of Contact less Tachometer Based Cyber Physical System -- Optimization of Loss Function on Human Faces Using Generative Adversarial Networks.

This book discusses various machine learning applications and models, developed using heterogeneous data, which helps in a comprehensive prediction, optimization, association analysis, cluster analysis and classification-related applications for various activities in urban area. It details multiple types of data generating from urban activities and suitability of various machine learning algorithms for handling urban data. The book is helpful for researchers, academicians, faculties, scientists and geospatial industry professionals for their research work and sets new ideas in the field of urban computing.

ISBN: 9789811609350

Standard No.: 10.1007/978-981-16-0935-0doiSubjects--Topical Terms:

3338351
Smart cities.

LC Class. No.: TD159.4 / .M334 2021

Dewey Class. No.: 628.0285

Machine learning approaches for urban computing
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520 $a This book discusses various machine learning applications and models, developed using heterogeneous data, which helps in a comprehensive prediction, optimization, association analysis, cluster analysis and classification-related applications for various activities in urban area. It details multiple types of data generating from urban activities and suitability of various machine learning algorithms for handling urban data. The book is helpful for researchers, academicians, faculties, scientists and geospatial industry professionals for their research work and sets new ideas in the field of urban computing.
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