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Quantum-inspired intelligent systems...

Bhattacharyya, Siddhartha, (1975-)

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Quantum-inspired intelligent systems for multimedia data analysis

Record Type:	Electronic resources : Monograph/item
Title/Author:	Quantum-inspired intelligent systems for multimedia data analysis/ Siddhartha Bhattacharyya, editor.
other author:	Bhattacharyya, Siddhartha,
Published:	Hershey, Pennsylvania :IGI Global, : [2018],
Description:	1 online resource (xix, 329 p.)
[NT 15003449]:	Chapter 1. Quantum-computing-inspired algorithms in machine learning -- Chapter 2. Quantum-inspired automatic clustering technique using ant colony optimization algorithm -- Chapter 3. True color image segmentation using quantum-induced modified-genetic-algorithm-based FCM algorithm -- Chapter 4. Hardware implementation of a visual image watermarking scheme using qubit/quantum computation through reversible methodology -- Chapter 5. Grayscale image segmentation with quantum-inspired multilayer self-organizing neural network architecture endorsed by context sensitive thresholding -- Chapter 6. Landcover change detection using PSO-evaluated quantum CA approach on multi-temporal remote-sensing watershed images -- Chapter 7. True color image segmentation by MUSIG activation function using self-supervised QMLSONN architecture with context-sensitive thresholding -- Chapter 8. An efficient handwritten character recognition using quantum multilayer neural network (QMLNN) architecture: quantum multilayer neural network -- Chapter 9. A quantum neurois data analytics architecture for the usability evaluation of learning management systems.
Subject:	Multimedia data mining. -
Online resource:	http://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/978-1-5225-5219-2
ISBN:	9781522552208 (ebook)

Quantum-inspired intelligent systems for multimedia data analysis
Quantum-inspired intelligent systems for multimedia data analysis[electronic resource] /Siddhartha Bhattacharyya, editor. - Hershey, Pennsylvania :IGI Global,[2018] - 1 online resource (xix, 329 p.)

Includes bibliographical references and index.

Chapter 1. Quantum-computing-inspired algorithms in machine learning -- Chapter 2. Quantum-inspired automatic clustering technique using ant colony optimization algorithm -- Chapter 3. True color image segmentation using quantum-induced modified-genetic-algorithm-based FCM algorithm -- Chapter 4. Hardware implementation of a visual image watermarking scheme using qubit/quantum computation through reversible methodology -- Chapter 5. Grayscale image segmentation with quantum-inspired multilayer self-organizing neural network architecture endorsed by context sensitive thresholding -- Chapter 6. Landcover change detection using PSO-evaluated quantum CA approach on multi-temporal remote-sensing watershed images -- Chapter 7. True color image segmentation by MUSIG activation function using self-supervised QMLSONN architecture with context-sensitive thresholding -- Chapter 8. An efficient handwritten character recognition using quantum multilayer neural network (QMLNN) architecture: quantum multilayer neural network -- Chapter 9. A quantum neurois data analytics architecture for the usability evaluation of learning management systems.

Restricted to subscribers or individual electronic text purchasers.

"This book brings a broad spectrum of artificial intelligence and its applications under the purview of multimedia information processing so that it is able to trigger further inspiration among various research communities to contribute in their respective fields of applications thereby orienting these application fields towards faithful understanding of multimedia data"--

ISBN: 9781522552208 (ebook)Subjects--Topical Terms:

3251475
Multimedia data mining.

LC Class. No.: QA76.9.D343 / Q365 2018e

Dewey Class. No.: 006.7

Quantum-inspired intelligent systems for multimedia data analysis
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020 $a 9781522552208 (ebook)
020 $a 9781522552192 (hardcover)
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245 0 0 $a Quantum-inspired intelligent systems for multimedia data analysis $h [electronic resource] / $c Siddhartha Bhattacharyya, editor.
260 $a Hershey, Pennsylvania : $b IGI Global, $c [2018]
300 $a 1 online resource (xix, 329 p.)
504 $a Includes bibliographical references and index.
505 0 $a Chapter 1. Quantum-computing-inspired algorithms in machine learning -- Chapter 2. Quantum-inspired automatic clustering technique using ant colony optimization algorithm -- Chapter 3. True color image segmentation using quantum-induced modified-genetic-algorithm-based FCM algorithm -- Chapter 4. Hardware implementation of a visual image watermarking scheme using qubit/quantum computation through reversible methodology -- Chapter 5. Grayscale image segmentation with quantum-inspired multilayer self-organizing neural network architecture endorsed by context sensitive thresholding -- Chapter 6. Landcover change detection using PSO-evaluated quantum CA approach on multi-temporal remote-sensing watershed images -- Chapter 7. True color image segmentation by MUSIG activation function using self-supervised QMLSONN architecture with context-sensitive thresholding -- Chapter 8. An efficient handwritten character recognition using quantum multilayer neural network (QMLNN) architecture: quantum multilayer neural network -- Chapter 9. A quantum neurois data analytics architecture for the usability evaluation of learning management systems.
506 $a Restricted to subscribers or individual electronic text purchasers.
520 3 $a "This book brings a broad spectrum of artificial intelligence and its applications under the purview of multimedia information processing so that it is able to trigger further inspiration among various research communities to contribute in their respective fields of applications thereby orienting these application fields towards faithful understanding of multimedia data"-- $c Provided by publisher.
650 0 $a Multimedia data mining. $3 3251475
650 0 $a Artificial intelligence. $3 516317
650 0 $a Quantum logic. $3 710562
700 1 $a Bhattacharyya, Siddhartha, $d 1975- $e editor. $3 3231407
856 4 0 $u http://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/978-1-5225-5219-2