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Vision, sensing and analyticsintegra...

Ahad, Md Atiqur Rahman.

Vision, sensing and analyticsintegrative approaches /

Record Type:	Electronic resources : Monograph/item
Title/Author:	Vision, sensing and analyticsedited by Md Atiqur Rahman Ahad, Atsushi Inoue.
Reminder of title:	integrative approaches /
other author:	Ahad, Md Atiqur Rahman.
Published:	Cham :Springer International Publishing :2021.
Description:	x, 413 p. :ill., digital ;24 cm.
Contained By:	Springer Nature eBook
Subject:	Computer vision.
Online resource:	https://doi.org/10.1007/978-3-030-75490-7
ISBN:	9783030754907$q(electronic bk.)

Vision, sensing and analyticsintegrative approaches /
Vision, sensing and analyticsintegrative approaches /[electronic resource] :edited by Md Atiqur Rahman Ahad, Atsushi Inoue. - Cham :Springer International Publishing :2021. - x, 413 p. :ill., digital ;24 cm. - Intelligent systems reference library,v.2071868-4394 ;. - Intelligent systems reference library ;v.24..

Deep Architectures in Visual Transfer Learning -- Deep Reinforcement Learning: A New Frontier in Computer Vision Research -- Deep Learning for Data-driven Predictive Maintenance -- Multi-Criteria Fuzzy Goal Programming under Multi-Uncertainty -- Skeleton-based Human Action Recognition on Large-Scale Datasets.

This book serves as the first guideline of the integrative approach, optimal for our new and young generations. Recent technology advancements in computer vision, IoT sensors, and analytics open the door to highly impactful innovations and applications as a result of effective and efficient integration of those. Such integration has brought to scientists and engineers a new approach --the integrative approach. This offers far more rapid development and scalable architecting when comparing to the traditional hardcore developmental approach. Featuring biomedical and healthcare challenges including COVID-19, we present a collection of carefully selective cases with significant added- values as a result of integrations, e.g., sensing with AI, analytics with different data sources, and comprehensive monitoring with many different sensors, while sustaining its readability.

ISBN: 9783030754907$q(electronic bk.)

Standard No.: 10.1007/978-3-030-75490-7doiSubjects--Topical Terms:

200113
Computer vision.

LC Class. No.: TA1634 / .V575 2021

Dewey Class. No.: 006.37

Vision, sensing and analyticsintegrative approaches /
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300 $a x, 413 p. : $b ill., digital ; $c 24 cm.
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505 0 $a Deep Architectures in Visual Transfer Learning -- Deep Reinforcement Learning: A New Frontier in Computer Vision Research -- Deep Learning for Data-driven Predictive Maintenance -- Multi-Criteria Fuzzy Goal Programming under Multi-Uncertainty -- Skeleton-based Human Action Recognition on Large-Scale Datasets.
520 $a This book serves as the first guideline of the integrative approach, optimal for our new and young generations. Recent technology advancements in computer vision, IoT sensors, and analytics open the door to highly impactful innovations and applications as a result of effective and efficient integration of those. Such integration has brought to scientists and engineers a new approach --the integrative approach. This offers far more rapid development and scalable architecting when comparing to the traditional hardcore developmental approach. Featuring biomedical and healthcare challenges including COVID-19, we present a collection of carefully selective cases with significant added- values as a result of integrations, e.g., sensing with AI, analytics with different data sources, and comprehensive monitoring with many different sensors, while sustaining its readability.
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650 0 $a Remote sensing. $3 195948
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950 $a Intelligent Technologies and Robotics (SpringerNature-42732)