05718nam 2201417z- 450 991063998510332120231214133044.03-0365-6062-9(CKB)5470000001633503(oapen)https://directory.doabooks.org/handle/20.500.12854/95825(EXLCZ)99547000000163350320202301d2022 |y 0engurmn|---annantxtrdacontentcrdamediacrrdacarrierAugmented Reality, Virtual Reality & Semantic 3D ReconstructionBaselMDPI - Multidisciplinary Digital Publishing Institute20221 electronic resource (304 p.)3-0365-6061-0 Augmented reality is a key technology that will facilitate a major paradigm shift in the way users interact with data and has only just recently been recognized as a viable solution for solving many critical needs. In practical terms, this innovation can be used to visualize data from hundreds of sensors simultaneously, overlaying relevant and actionable information over your environment through a headset. Semantic 3D reconstruction unlocks the promise of AR technology, possessing a far greater availability of semantic information. Although, there are several methods currently available as post-processing approaches to extract semantic information from the reconstructed 3D models, the results obtained results have been uncertain and evenly incorrect. Thus, it is necessary to explore or develop a novel 3D reconstruction approach to automatically recover 3D geometry model and obtained semantic information simultaneously. The rapid advent of deep learning brought new opportunities to the field of semantic 3D reconstruction from photo collections. Deep learning-based methods are not only able to extract semantic information but can also enhance fundamental techniques in semantic 3D reconstruction, techniques which include feature matching or tracking, stereo matching, camera pose estimation, and use of multi-view stereo methods. Moreover, deep learning techniques can be used to extract priors from photo collections, and this obtained information can in turn improve the quality of 3D reconstruction.Technology: general issuesbicsscHistory of engineering & technologybicsscfeature trackingsuperpixelstructure from motionthree-dimensional reconstructionlocal featuremulti-view stereoconstruction hazardsafety educationphotorealityvirtual realityanatomizationaudio classificationolfactory displaydeep learningtransfer learninginception modelaugmented realityhigher educationscientific productionweb of sciencebibliometric analysisscientific mappingapplications in subject areasinteractive learning environments3P modelprimary educationeducational technologymobile lip reading systemlightweight neural networkface correctionvirtual reality (VR)computer visionprojection mapping3D face modelsuper-resolutionradial curveDynamic Time Warpingsemantic 3D reconstructioneye-in-hand vision systemrobotic manipulatorprobabilistic fusiongraph-based refinement3D modelling3D representationgame enginelaser scanningpanoramic photographysuper-resolution reconstructiongenerative adversarial networksdense convolutional networkstexture lossWGAN-GPorientationpositioningviewpointimage matchingalgorithmtransformationADHDEDAHassessmentcontinuous performance testPhotometric Stereo (PS)3D reconstructionfully convolutional network (FCN)semi-immersive virtual realitychildrencooperative gamesempowermentperceptionmotor planningproblem-solvingarea of interestwayfindingspatial informationone-shot learninggesture recognitionGRENskeleton-based3D compositionpre-visualizationstereo vision360° videoTechnology: general issuesHistory of engineering & technologyLv Zhihanedt1217078Wang Jing-YanedtKumar NeerajedtLloret JaimeedtLv ZhihanothWang Jing-YanothKumar NeerajothLloret JaimeothBOOK9910639985103321Augmented Reality, Virtual Reality & Semantic 3D Reconstruction3014583UNINA04704nam 2200613Ia 450 991087726590332120200520144314.00-470-48545-01-119-19753-81-282-36866-497866123686600-470-48544-2(CKB)1000000000747715(EBL)433889(OCoLC)428132248(SSID)ssj0000116360(PQKBManifestationID)11874908(PQKBTitleCode)TC0000116360(PQKBWorkID)10035942(PQKB)10939228(MiAaPQ)EBC433889(EXLCZ)99100000000074771520090211d2009 uy 0engur|n|---|||||txtccrBusiness valuation discounts and premiums /Shannon P. Pratt2nd ed.Hoboken, NJ Wileyc20091 online resource (505 p.)Description based upon print version of record.0-470-37148-X Includes bibliographical references and index.Business Valuation: Discounts and Premiums, Second Edition; Contents; List of Exhibits; About the Author; About the Contributing Authors; Foreword; Preface; Acknowledgments; Chapter 1: Overview of Business Valuation Discounts and Premiums and the Bases to Which They Are Applied; Chapter 2: Minority Discounts and Control Premiums; Chapter 3: Empirical Data Regarding Minority Discounts and Control Premiums; Chapter 4: Minority Discounts and Control Premiums in the Courts; Chapter 5: Discounts for Lack of Marketability for Minority Interests: Concept and EvidenceChapter 6: Synopsis of Restricted Stock StudiesChapter 7: LiquiStat Database (Restricted Stocks, Options, Warrants, and Convertible Securities); Chapter 8: Blockage Discounts; Chapter 9: John Emory Pre-Initial Public Offering Discount for Lack of Marketability Studies-Complete Underlying Data; Chapter 10: Valuation Advisors Discount for Lack of Marketability Study; Chapter 11: Factors Affecting Discounts for Lack of Marketability for Minority Interests; Chapter 12: Discounts for Lack of Marketability for Controlling InterestsChapter 13: The Quantitative Marketability Discount Model: A Shareholder Level DCF ModelChapter 14: Marketability Discounts in the Courts-Minority Interests; Chapter 15: Marketability Discounts in the Courts-Controlling Interests; Chapter 16: Voting versus Nonvoting Stock; Chapter 17: Key Person Discounts and Premiums; Chapter 18: Discounts for Trapped-In Capital Gains Taxes; Chapter 19: Nonhomogeneous Assets (''Portfolio'') Discounts; Chapter 20: Discounts for Environmental, Litigation, and Other Contingent LiabilitiesChapter 21: Discount Adjustments for Limited Partnership Interests and Other Asset Management EntitiesChapter 22: Adjusting Values for Differences in Size; Chapter 23: Discounts and Premiums in ESOP Valuations; Chapter 24: Discounts and Premiums in Divorce Disputes; Chapter 25: Discounts and Premiums in Corporate and Partnership Dissolution and Oppression Cases; Chapter 26: Discounts and Premiums in Fair Value for Financial Reporting; Chapter 27: Premium and Discount Issues in Undivided Interest Valuations; Chapter 28: Common Errors in Applying Discounts and Premiums; Appendix A: BibliographyAppendix B: Data ResourcesAppendix C: How Much Can Marketability Affect Security Values?; Appendix D: Internal Revenue Service Revenue Ruling 77-287; Appendix E: Securities and Exchange Commission Rules 144 and 144A; Appendix F: Table of Cases; IndexLeading authority Shannon Pratt demystifies discounts and premiums in business valuation ""A must-read! Shannon Pratt continues to add to the business valuation body of knowledge."" -Jay Fishman, FASA There is often more money in dispute in determining the discounts and premiums in a business valuation than in arriving at the pre-discount value itself. Discounts and premiums affect not only the value of the company, but also play a crucial role in determining the risk involved, control issues, marketability, and contingent liability, to name a few. Approaching a business vaBusiness enterprisesValuationBusinessValuationBusiness enterprisesValuation.BusinessValuation.658.15Pratt Shannon P116635MiAaPQMiAaPQMiAaPQBOOK9910877265903321Business valuation discounts and premiums4203871UNINA