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Kinesthetic perception = a machine l...
~
Chaudhuri, Subhasis.
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Kinesthetic perception = a machine learning approach /
Record Type:
Electronic resources : Monograph/item
Title/Author:
Kinesthetic perception/ by Subhasis Chaudhuri, Amit Bhardwaj.
Reminder of title:
a machine learning approach /
Author:
Chaudhuri, Subhasis.
other author:
Bhardwaj, Amit.
Published:
Singapore :Springer Singapore : : 2018.,
Description:
xv, 138 p. :ill., digital ;24 cm.
Contained By:
Springer eBooks
Subject:
Haptic devices. -
Online resource:
http://dx.doi.org/10.1007/978-981-10-6692-4
ISBN:
9789811066924
Kinesthetic perception = a machine learning approach /
Chaudhuri, Subhasis.
Kinesthetic perception
a machine learning approach /[electronic resource] :by Subhasis Chaudhuri, Amit Bhardwaj. - Singapore :Springer Singapore :2018. - xv, 138 p. :ill., digital ;24 cm. - Studies in computational intelligence,v.7481860-949X ;. - Studies in computational intelligence ;v.748..
This book focuses on the study of possible adaptive sampling mechanisms for haptic data compression aimed at applications like tele-operations and tele-surgery. Demonstrating that the selection of the perceptual dead zones is a non-trivial problem, it presents an exposition of various issues that researchers must consider while designing compression algorithms based on just noticeable difference (JND) The book begins by identifying perceptually adaptive sampling strategies for 1-D haptic signals, and goes on to extend the findings on multidimensional signals to study directional sensitivity, if any. The book also discusses the effect of the rate of change of kinesthetic stimuli on the JND, temporal resolution for the perceivability of kinesthetic force stimuli, dependence of kinesthetic perception on the task being performed, the sequential effect on kinesthetic perception, and, correspondingly, on the perceptual dead zone. Offering a valuable resource for researchers, professionals, and graduate students working on haptics and machine perception studies, the book can also support interdisciplinary work focused on automation in surgery.
ISBN: 9789811066924
Standard No.: 10.1007/978-981-10-6692-4doiSubjects--Topical Terms:
1084619
Haptic devices.
LC Class. No.: QA76.9.H85
Dewey Class. No.: 004.77
Kinesthetic perception = a machine learning approach /
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This book focuses on the study of possible adaptive sampling mechanisms for haptic data compression aimed at applications like tele-operations and tele-surgery. Demonstrating that the selection of the perceptual dead zones is a non-trivial problem, it presents an exposition of various issues that researchers must consider while designing compression algorithms based on just noticeable difference (JND) The book begins by identifying perceptually adaptive sampling strategies for 1-D haptic signals, and goes on to extend the findings on multidimensional signals to study directional sensitivity, if any. The book also discusses the effect of the rate of change of kinesthetic stimuli on the JND, temporal resolution for the perceivability of kinesthetic force stimuli, dependence of kinesthetic perception on the task being performed, the sequential effect on kinesthetic perception, and, correspondingly, on the perceptual dead zone. Offering a valuable resource for researchers, professionals, and graduate students working on haptics and machine perception studies, the book can also support interdisciplinary work focused on automation in surgery.
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Engineering (Springer-11647)
based on 0 review(s)
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W9340496
電子資源
11.線上閱覽_V
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EB QA76.9.H85
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