| 000 | 04895cam a2200721 i 4500 | ||
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| 001 | on1083673341 | ||
| 003 | OCoLC | ||
| 005 | 20220711203500.0 | ||
| 006 | m o d | ||
| 007 | cr cnu---unuuu | ||
| 008 | 190126t20192019njua ob 001 0 eng c | ||
| 010 | _a 2019004054 | ||
| 040 |
_aYUS _beng _cYUS _dOCLCF _dN$T _dEBLCP _dYDX _dDG1 _dUIU _dRECBK _dDLC _dOCLCO _dUKAHL |
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| 019 | _a1104796068 | ||
| 020 |
_a9781119488781 _qelectronic book |
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| 020 |
_a1119488788 _qelectronic book |
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| 020 |
_a9781119488774 _qelectronic book |
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| 020 |
_a111948877X _qelectronic book |
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| 020 |
_z9781119488750 _qhardcover |
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| 020 |
_z1119488753 _qhardcover |
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| 020 |
_a9781119488767 _q(electronic bk.) |
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| 020 |
_a1119488761 _q(electronic bk.) |
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| 024 | 8 | _a16278992 | |
| 029 | 1 |
_aCHNEW _b001055885 |
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| 035 |
_a(OCoLC)1083673341 _z(OCoLC)1104796068 |
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| 042 | _apcc | ||
| 050 | 4 |
_aTA1638.4 _b.D49 2019 |
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| 072 | 7 |
_aCOM _x000000 _2bisacsh |
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| 082 | 0 | 0 |
_a006.4/2015181 _223 |
| 090 |
_aTA1638.4 _b.D49 2019 (LC) |
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| 049 | _aMAIN | ||
| 100 | 1 |
_aDey, Sandip, _d1977- _98090 |
|
| 245 | 1 | 0 |
_aQuantum inspired meta-heuristics for image analysis _h[electronic resource] / _cSandip Dey, Siddhartha Bhattacharyya, Ujjwal Maulik. |
| 264 | 1 |
_aHoboken, NJ : _bJohn Wiley & Sons, Inc., _c2019. |
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| 264 | 4 | _c©2019 | |
| 300 | _a1 online resource ( xvi, 358 pages) | ||
| 336 |
_atext _btxt _2rdacontent |
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| 337 |
_acomputer _bc _2rdamedia |
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| 338 |
_aonline resource _bcr _2rdacarrier |
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| 504 | _aIncludes bibliographical references and index. | ||
| 588 | _aDescription based on online resource; title from digital title page (viewed on August 14, 2019). | ||
| 520 | _aIntroduces quantum inspired techniques for image analysis for pure and true gray scale/color images in a single/multi-objective environment This book will entice readers to design efficient meta-heuristics for image analysis in the quantum domain. It introduces them to the essence of quantum computing paradigm, its features, and properties, and elaborates on the fundamentals of different meta-heuristics and their application to image analysis. As a result, it will pave the way for designing and developing quantum computing inspired meta-heuristics to be applied to image analysis. Quantum Inspired Meta-heuristics for Image Analysis begins with a brief summary on image segmentation, quantum computing, and optimization. It also highlights a few relevant applications of the quantum based computing algorithms, meta-heuristics approach, and several thresholding algorithms in vogue. Next, it discusses a review of image analysis before moving on to an overview of six popular meta-heuristics and their algorithms and pseudo-codes. Subsequent chapters look at quantum inspired meta-heuristics for bi-level and gray scale multi-level image thresholding; quantum behaved meta-heuristics for true color multi-level image thresholding; and quantum inspired multi-objective algorithms for gray scale multi-level image thresholding. Each chapter concludes with a summary and sample questions. -Provides in-depth analysis of quantum mechanical principles -Offers comprehensive review of image analysis -Analyzes different state-of-the-art image thresholding approaches -Detailed current, popular standard meta-heuristics in use today -Guides readers step by step in the build-up of quantum inspired meta-heuristics -Includes a plethora of real life case studies and applications -Features statistical test analysis of the performances of the quantum inspired meta-heuristics vis-A-vis their conventional counterparts Quantum Inspired Meta-heuristics for Image Analysis is an excellent source of information for anyone working with or learning quantum inspired meta-heuristics for image analysis. | ||
| 650 | 0 |
_aImage segmentation. _98091 |
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| 650 | 0 |
_aImage analysis. _96891 |
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| 650 | 0 |
_aMetaheuristics. _94799 |
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| 650 | 0 |
_aHeuristic algorithms. _94883 |
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| 650 | 7 |
_aCOMPUTERS / General _2bisacsh _95150 |
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| 650 | 7 |
_aHeuristic algorithms. _2fast _0(OCoLC)fst01749726 _94883 |
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| 650 | 7 |
_aImage analysis. _2fast _0(OCoLC)fst00967482 _96891 |
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| 650 | 7 |
_aImage segmentation. _2fast _0(OCoLC)fst01909702 _98091 |
|
| 650 | 7 |
_aMetaheuristics. _2fast _0(OCoLC)fst02000551 _94799 |
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| 655 | 0 |
_aElectronic books. _93294 |
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| 655 | 4 |
_aElectronic books. _93294 |
|
| 700 | 1 |
_aBhattacharyya, Siddhartha, _d1975- _98092 |
|
| 700 | 1 |
_aMaulik, Ujjwal. _0http://id.loc.gov/authorities/names/n2008180067 _98093 |
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| 710 | 2 |
_aWiley InterScience (Online service) _96290 |
|
| 776 | 0 | 8 |
_iPrint version: _aDey, Sandip, 1977- author. _tQuantum inspired meta-heuristics for image analysis _dHoboken, NJ : Wiley, 2019 _z9781119488750 _w(DLC) 2019001402 |
| 856 | 4 | 0 |
_uhttps://doi.org/10.1002/9781119488767 _zWiley Online Library |
| 942 | _cEBK | ||
| 994 |
_a92 _bDG1 |
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| 999 |
_c69019 _d69019 |
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