LEADER 04507nam 2200517 450 001 9910798288903321 005 20230124193612.0 010 $a1-68108-110-5 035 $a(CKB)3710000000627710 035 $a(EBL)4504167 035 $a(MiAaPQ)EBC4504167 035 $a(Au-PeEL)EBL4504167 035 $a(CaPaEBR)ebr11204299 035 $a(OCoLC)948924362 035 $a(EXLCZ)993710000000627710 100 $a20160503h20162016 uy 0 101 0 $aeng 135 $aur|n|---||||| 181 $2rdacontent 182 $2rdamedia 183 $2rdacarrier 200 00$aAdvances in face image analysis $etheory and application /$fedited by Fadi Dornaika ; contributors Ammar Assoum [and fifteen others] 210 1$aSharjah, United Arab Emirates :$cBentham Science Publishers,$d2016. 210 4$d©2016 215 $a1 online resource (264 p.) 300 $aDescription based upon print version of record. 311 $a1-68108-111-3 320 $aIncludes bibliographical references at the end of each chapters and index. 327 $aCONTENTS; FOREWORD ; PREFACE ; LIST OF CONTRIBUTORS ; Facial Expression Classification Based on Convolutional Neural Networks ; INTRODUCTION; Convolutional Neural Networks; Facial Expression Analysis; GRADIENT-BASED LEARNING FOR CNNS; FEATURE GENERALIZATION; EXPERIMENTS; Datasets; CK-Regianini Dataset; CK-Zheng Dataset; CMU-Pittsburgh dataset ; Experiments on CNN-based Facial Expression Classification; Design; Results and Analysis; Experiments on Feature Generalization; Design; Results and Analysis; DISCUSSION; CONFLICT OF INTEREST; ACKNOWLEDGEMENTS; REFERENCES 327 $aSparsity Preserving Projection Based Constrained Graph Embedding and Its Application to Face Recognition INTRODUCTION; RELATED WORK; Locality Preserving Projection; Neighborhood Preserving Embedding; Sparsity Preserving Projection; Constrained Graph Embedding; SPP BASED CONSTRAINED GRAPH EMBEDDING; SPP-CGE; Out-of-Sample Extension; EXPERIMENTAL RESULTS; CONCLUSION; NOTES; CONFLICT OF INTEREST; ACKNOWLEDGEMENTS; REFERENCES; Face Recognition Using Exponential Local Discriminant Embedding ; INTRODUCTION; Contribution and Related Work; REVIEW OF LOCAL DISCRIMINANT EMBEDDING (LDE) 327 $aIntrinsic Graph and Penalty GraphOptimal Mapping; The Small Sample Size Problem; EXPONENTIAL LDE; Matrix Exponential; Exponential LDE; THEORETICAL ANALYSIS OF ELDE; Solving the SSS Problem; Distance Diffusion Mapping; PERFORMANCE EVALUATION; Face Databases; Recognition Accuracy; Comparison between Regularized LDE and ELDE; CONCLUSION; NOTES; CONFLICT OF INTEREST; ACKNOWLEDGMENTS; REFERENCES; Adaptive Locality Preserving Projections for Face Recognition ; INTRODUCTION; LOCALITY PRESERVING PROJECTIONS; ENHANCED AND PARAMETERLESS LPP; PERFORMANCE EVALUATION; Face Databases; Experimental Results 327 $aPerformance Comparison for OLPP and SLPPCONCLUSION; NOTES; CONFLICT OF INTEREST; ACKNOWLEDGMENTS; REFERENCES; Face Recognition Using 3D Face Rectification ; INTRODUCTION; PROPOSED METHOD ; FACE DATABASE ; PREPROCESSING ; FACIAL FEATURE DETECTION ; POSE ESTIMATION; IRAD Contours; Ellipse Fitting And Roll Correction; Yaw Correction; Pitch Correction; Accuracy Of The Pose Estimation Method; ROTATION AND POST PROCESSING; EXPERIMENTS; CONCLUSION; NOTES; CONFLICT OF INTEREST; ACKNOWLEDGMENTS; REFERENCES; 3D Face Recognition ; INTRODUCTION; 3D FACE ACQUISITION; 3D FACE REPRESENTATION; PREPROCESSING 327 $a3D FACE ALIGNMENTFACE RECOGNITION; CONCLUDING REMARKS; CONFLICT OF INTEREST; ACKNOWLEDGEMENTS; REFERENCES; Model-Less 3D Face Pose Estimation ; INTRODUCTION; STATE OF THE ART; THE MACHINE LEARNING METHODOLOGY; Locality Preserving Projections; LPP Algorithm; Supervised Locality Preserving Projections; LABEL-SENSITIVE LOCALITY PRESERVING PROJECTION; Presetting:; Algorithm:; PROPOSED APPROACH: SPARSE GRAPH BASED LSLPP; EXPERIMENTAL RESULTS; CONCLUSION; NOTES; CONFLICT OF INTEREST; ACKNOWLEDGEMENTS; REFERENCES; Efficient Deformable 3D Face Model Fitting to Monocular Images ; INTRODUCTION 327 $aLIGHTWEIGHT FACIAL FEATURE DETECTION 606 $aHuman face recognition (Computer science) 615 0$aHuman face recognition (Computer science) 676 $a006.37 702 $aDornaika$b Fadi 702 $aAssoum$b Ammar 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910798288903321 996 $aAdvances in face image analysis$93674168 997 $aUNINA LEADER 03590oam 2200625 c 450 001 9910960936103321 005 20260102090118.0 010 $a3-8382-7533-0 024 3 $a9783838275338 035 $a(CKB)4100000011976439 035 $a(MiAaPQ)EBC6661486 035 $a(Au-PeEL)EBL6661486 035 $a(OCoLC)1259588403 035 $a(ibidem)9783838275338 035 $a(EXLCZ)994100000011976439 100 $a20260102d2021 uy 0 101 0 $aeng 135 $aurcz#---auuuu 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aFalse Mirrors: The Weaponization of Social Media in Russia?s Operation to Annex Crimea /$fAndrey Demartino, Andreas Umland, Oleksiy Danilov 205 $a1st ed. 210 $aHannover$cibidem$d2021 215 $a1 online resource (153 pages) 225 0 $aUkrainian Voices$v13 320 $aIncludes bibliographical references. 327 $aIntro -- Foreword -- Abstract -- Introduction -- 1. Background -- 1.1. Articles, News Items, Blogs -- 1.2. Western Studies -- 1.3. Ukrainian Studies -- 1.4. The "Ideological Problem" of Russian Historiography -- 2. The Crimean Internet in Figures: 2011-2014 -- 3. The Russian "Information Warfare Machine". The Main Actors -- 4. Russia's Activity. The Channels of Information Influence (October-December 2013) -- 4.1. Internet Forums -- 4.2. The GRU and Facebook -- 4.3. The Twitter of "Crimean Events" -- 4.4. The Blocking of Facebook -- 4.5. The Nationwide Anti-Ukrainian Campaign in Russia: The Crimean Dimension -- 5. The Ukrainian Response. Countermeasures Against Foreign Information Influence -- Conclusions -- References -- Appendix -- Short Biography of the Author. 330 $aIn his timely study, Andrii Demartino investigates the multitude of techniques how social media can be used to advance an aggressive foreign policy, as exemplified by the Russian Federation?s operation to annex Crimea in 2014. Drawing on a wide range of sources, Demartino traces the implementation of a series of Russian measures to create channels and organisations manipulating public opinion in the Ukrainian segment of the internet and on platforms such as Facebook, VKontakte, Odnoklassniki, LiveJournal, and Twitter. Addressing the pertinent question of how much the operation to annex Crimea was either improvised or planned, he draws attention to Russia?s ad-hoc actions in the sphere of social media in 2014. Based on an in-depth analysis of the methods of Russia?s influence operations, the book proposes a number of counterstrategies to prevent such ?active measures.? These propositions can serve to improve Ukraine?s national information policy as well as help to develop adequate security concepts of other states. 410 0$aUkrainian voices (Stuttgart, Germany) ;$v13. 606 $aUkraine 606 $aSocial Media 606 $aSoziale Medien 606 $aRussian Federation 606 $aRussische Föderation 606 $aAnnex Crimea 606 $aAnnexion Krim 615 4$aUkraine 615 4$aSocial Media 615 4$aSoziale Medien 615 4$aRussian Federation 615 4$aRussische Föderation 615 4$aAnnex Crimea 615 4$aAnnexion Krim 676 $a355.41 700 $aDemartino$b Andrey$4aut$01603414 702 $aUmland$b Andreas$4edt 702 $aDanilov$b Oleksiy$4aui 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910960936103321 996 $aFalse mirrors$93927779 997 $aUNINA