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[null,"1.","Record Nr.",null,"UNINA9910869175303321"]
[null,null,"Autore",null,"Burgess Andrew"]
[null,null,"Titolo",null,"The Executive Guide to Artificial Intelligence : Cutting Through the Hype - How to get the most from AI in your Organization / / by Andrew Burgess"]
[null,null,"Pubbl/distr/stampa",null,"Cham : , : Springer International Publishing : , : Imprint : Palgrave Macmillan, , 2024"]
[null,null,"ISBN",null,"9783031507229"]
[{"$nulls":4},"9783031507212"]
[null,null,"Edizione",null,"[2nd ed. 2024.]"]
[null,null,"Descrizione fisica",null,"1 online resource (181 pages)"]
[null,null,"Disciplina",null,"006.3"]
[null,null,"Soggetti",null,"Technological innovations"]
[{"$nulls":4},"Business"]
[{"$nulls":4},"Management science"]
[{"$nulls":4},"Artificial intelligence"]
[{"$nulls":4},"Innovation and Technology Management"]
[{"$nulls":4},"Business and Management"]
[{"$nulls":4},"Artificial Intelligence"]
[null,null,"Lingua di pubblicazione",null,"Inglese"]
[null,null,"Formato",null,"Materiale a stampa"]
[null,null,null,"Livello bibliografico","Monografia"]
[null,null,"Nota di contenuto",null,"1. Don’t Believe the Hype -- 2. Why Now? -- 3. AI Capabilities Framework -- 4. Associated Technologies -- 5. AI in Action -- 6. Starting an AI Journey -- 7. AI Prototyping -- 8. What Could Possibly Go Wrong? -- 9. Industrialising AI -- 10. Living with AI -- 11. Where Next for AI?."]
[null,null,null,"Sommario/riassunto","This book, now in a thoroughly revised and updated second edition, takes a pragmatic and hype–free approach to explaining artificial intelligence and how it can be utilised by businesses today. At the book's core is a framework which describes, in nontechnical language, the nine core capabilities of Artificial Intelligence (AI). Each of these capabilities, ranging from image recognition, through prediction, to Generative AI, is explained using real–life examples and how they can be applied in a business environment. The advent of Large Language Models has put AI front and centre of Board discussions. AI has the ability to deliver step–change benefits to organisations and enables forward–thinking business leaders to rethink their business models or create completely new businesses. But most of the real value of AI is "]
[{"$nulls":4},"hidden behind marketing hyperbole, confusing terminology, inflated expectations and dire warnings of ‘robot overlords’. Any business executive who wants to know how to exploit AI in their business today is left confused and frustrated. As an advisor in AI, Andrew Burgess regularly comes face–to–face with business executives who are struggling to cut through the AI and LLM hype. The knowledge and experience he has gained in advising them has provided him with the skills to help business executives understand what AI is and how they can exploit its many benefits. Through the distilled knowledge included in this book, business leaders will be able to take full advantage of this most disruptive of technologies and create substantial competitive advantage for their companies. A management consultant, author and speaker with over 30 years’ experience, Andrew is considered an authority on Artificial Intelligence. Through his business, GreenhouseAI, he advises organisations on their AI strategy, its application in business and its ethics, and is regularly invited to speak at conferences on these subjects. He is Visiting Senior Fellow in AI at Loughborough University and Expert-in-Residence for AI at Imperial College’s Enterprise Lab. He is a member of the AI Committee at the British Standards Institute."]
[null,"2.","Record Nr.",null,"UNINA9910962414403321"]
[null,null,"Titolo",null,"Private law and human rights : bringing rights home in Scotland and South Africa / / edited by Elspeth Reid and Daniel Visser"]
[null,null,"Pubbl/distr/stampa",null,"Edinburgh, : Edinburgh University Press, 2013"]
[null,null,"ISBN",null,"9780748684182"]
[{"$nulls":4},"0748684182"]
[null,null,"Edizione",null,"[1st ed.]"]
[null,null,"Descrizione fisica",null,"1 online resource (577 p.)"]
[null,null,"Disciplina",null,"344.1107"]
[null,null,"Soggetti",null,"Civil rights - Scotland"]
[{"$nulls":4},"Civil rights - South Africa"]
[{"$nulls":4},"Civil law - Scotland"]
[{"$nulls":4},"Civil law - South Africa"]
[null,null,"Lingua di pubblicazione",null,"Inglese"]
[null,null,"Formato",null,"Materiale a stampa"]
[null,null,null,"Livello bibliografico","Monografia"]
[null,null,null,"Note generali","Description based upon print version of record."]
[null,null,null,"Nota di bibliografia","Includes bibliographical references and index."]
[null,null,"Nota di contenuto",null,"Title Page; Imprint; Contents; Preface; Contributors; Table of Cases; Table of Statutes; Chapter 1 Introduction; Chapter 2 Private Law in the Age of Rights; Chapter 3 The Politics of Private Law: Sexual Minority Freedom in South Africa and Scotland; Chapter 4 Child Law: Respecting the Rights of Children; Chapter 5 Property Deprivation of an Absentee in Emulation of the Laws of Succession: The Laws of Scotland and South Africa Compared; Chapter 6 The Right to Personal Security; Chapter 7 Privacy ; Chapter 8 Defamation and Freedom of Expression; Chapter 9 Strict Liability"]
[{"$nulls":4},"Chapter 10 Liability of Public Authorities and Public OfficialsChapter 11 Nuisance; Chapter 12 Contract Law and Human Rights; Chapter 13 Principles, Policy and Practice: Human Rights and the Law of Contract; Chapter 14 Juristic Persons and Fundamental Rights; Chapter 15 Examining the Labour Law and Social Dimension of Human Rights: The UK and South Africa; Chapter 16 Rights in Security ;  Chapter 17 Access to Credit, the Law of Suretyship and Unfair Suretyships; Chapter 18 The Human Right of Property in Land Law: Comparing South Africa and Scotland"]
[{"$nulls":4},"Chapter 19 The Margin of Appreciation Doctrine of the European Court of Human Rights: Protection of Ownership and the Right to a HomeChapter 20 Environment and Human Rights: The Right to Water in South Africa and Scotland; Index"]
[null,null,null,"Sommario/riassunto","A comparative investigation into the revolution in private law in the era of human rights Scotland and South Africa are mixed jurisdictions, combining features of common law and civil law traditions. Over the last decade a shared feature in both Scotland and South Africa has been a new and intense focus on human rights. In Scotland the European Convention on Human Rights now constitutes an important element in the foundation of all domestic law. Similarly, the Constitution of the Republic of South Africa, adopted in 1996, has as its cornerstone a Bill of Rights that binds not only the legislat"]
[null,"3.","Record Nr.",null,"UNINA9910481962203321"]
[null,null,"Titolo",null,"MultiMedia Modeling : 22nd International Conference, MMM 2016, Miami, FL, USA, January 4-6, 2016, Proceedings, Part II / / edited by Qi Tian, Nicu Sebe, Guo-Jun Qi, Benoit Huet, Richang Hong, Xueliang Liu"]
[null,null,"Pubbl/distr/stampa",null,"Cham : , : Springer International Publishing : , : Imprint : Springer, , 2016"]
[null,null,"ISBN",null,"3-319-27674-3"]
[null,null,"Edizione",null,"[1st ed. 2016.]"]
[null,null,"Descrizione fisica",null,"1 online resource (XXIII, 433 p. 185 illus. in color.)"]
[null,null,"Collana",null,"Information Systems and Applications, incl. Internet/Web, and HCI, , 2946-1642 ; ; 9517"]
[null,null,"Disciplina",null,"006.7"]
[null,null,"Soggetti",null,"Multimedia systems"]
[{"$nulls":4},"Information storage and retrieval systems"]
[{"$nulls":4},"Pattern recognition systems"]
[{"$nulls":4},"Data mining"]
[{"$nulls":4},"Application software"]
[{"$nulls":4},"Multimedia Information Systems"]
[{"$nulls":4},"Information Storage and Retrieval"]
[{"$nulls":4},"Automated Pattern Recognition"]
[{"$nulls":4},"Data Mining and Knowledge Discovery"]
[{"$nulls":4},"Computer and Information Systems Applications"]
[null,null,"Lingua di pubblicazione",null,"Inglese"]
[null,null,"Formato",null,"Materiale a stampa"]
[null,null,null,"Livello bibliografico","Monografia"]
[null,null,null,"Note generali","Bibliographic Level Mode of Issuance: Monograph"]
[null,null,"Nota di contenuto",null,"Intro -- Preface -- Organization -- Contents - Part II -- Contents - Part I -- Special Session Poster Papers (continued) -- Transfer Nonnegative Matrix Factorization for Image Representation -- 1 Introduction -- 2 Related Work -- 3 Preliminaries -- 3.1 Nonnegative Matrix Factorization -- 3.2 Hessian Regularization -- 4 Transfer Nonnegative Matrix Factorization -- 4.1 Problem Definition -- 4.2 Proposed Approach -- 4.3 Optimization -- 5 Experiments -- 5.1 Dataset Description -- 5.2 Performance on Cross-Domain Datasets -- 6 Conclusion -- References -- Sentiment Analysis on Multi-View Social Data -- 1 Introduction -- 2 Related Works -- 2.1 Sentiment Analysis Datasets -- 2.2 Sentiment Analysis Approaches -- 3 The MVSA Dataset -- 3.1 Data Collection and Annotation -- 3.2 Data Analysis -- 4 Predicting Sentiment in Multi-view Data -- 4.1 Text-Based Approaches -- 4.2 Visual-Based Approaches -- 4.3 Multi-view Sentiment Analysis "]
[{"$nulls":4},"-- 5 Experiments -- 5.1 Results on Textual Messages -- 5.2 Results on Images -- 5.3 Results on Multi-View Data -- 6 Conclusion and Future Work -- References -- Single Image Super-Resolution via Convolutional Neural Network and Total Variation Regularization -- Abstract -- 1 Introduction -- 2 Overview of the SR Algorithm -- 3 Convolutional Neural Network for SR -- 3.1 Training Set Generation -- 3.2 Convolutional Neural Network for SR -- 4 Regularization Constraints for SR -- 4.1 Non-Local Similarity Regularization Constraint -- 4.2 Local Similarity Regularization Constraint -- 4.3 Fundamental Formula -- 5 Experimental Results -- 5.1 Datasets -- 5.2 Results and Comparison -- 6 Conclusion -- References -- An Effective Face Verification Algorithm to Fuse Complete Features in Convolutional Neural Network -- Abstract -- 1 Introduction -- 2 Related Work -- 3 Methodology -- 3.1 Network Structure -- 3.2 Feature Extraction -- 3.3 Verification."]
[{"$nulls":4},"4 Experiments -- 5 Conclusion -- References -- Driver Fatigue Detection System Based on DSP Platform -- Abstract -- 1 Introduction -- 2 Methodology -- 2.1 Face Detection -- 2.2 Eye Detection -- 2.3 Eye State Estimation -- 3 Experiment and Results -- 3.1 Experiment Setting -- 3.2 Experimental Results -- 4 Conclusion -- References -- Real-Time Grayscale-Thermal Tracking via Laplacian Sparse Representation -- 1 Introduction -- 2 Related Work -- 3 Bayesian Filtering for Object Tracking -- 4 Observation Model -- 4.1 Laplacian Sparse Representation -- 4.2 Candidate Likelihood -- 5 Experiments -- 5.1 Evaluation Settings -- 5.2 Evaluation Metrics -- 5.3 Comparison Results -- 5.4 Component Analysis -- 6 Conclusion -- References -- Efficient Perceptual Region Detector Based on Object Boundary -- 1 Introduction -- 2 Related Work -- 2.1 Superpixel -- 2.2 Local Detectors -- 2.3 General Object Proposal -- 3 CAR: The Method -- 3.1 Contour-Aware Superpixel (CAS) -- 3.2 Perceptual Regions Detection -- 4 Experiments -- 4.1 Under-Segmentation Error -- 4.2 Boundary Recall -- 4.3 CAR Detector Repeatability -- 5 Conclusions -- References -- 1D Barcode Region Detection Based on the Hough Transform and Support Vector Machine -- Abstract -- 1 Introduction -- 2 Proposed Method -- 2.1 Barcode Detection -- 2.2 Support Vector Machine -- 2.3 Hough Transform -- 2.4 Using the SVM Classifier to Judge Pieces of the Image -- 2.5 Post-processing -- 3 Experiments and Results Analysis -- 3.1 Datasets -- 3.2 Result -- 4 Conclusion -- Acknowledgment -- References -- Special Session Papers -- Client-Driven Strategy of Large-Scale Scene Streaming -- 1 Introduction -- 2 Related Works -- 3 Overview -- 4 Multiple-resolution 3D Space Adaptive Grid Creation -- 5 Scene Streaming Assemble Strategy -- 5.1 Dynamic Double Layer AOI (D-DLAOI) -- 5.2 Object Priority Determination and LOD Resolution."]
[{"$nulls":4},"6 Experimental Results -- 7 Conclusion and Future Work -- References -- SELSH: A Hashing Scheme for Approximate Similarity Search with Early Stop Condition -- 1 Introduction -- 2 Preliminaries -- 2.1 Problem Definition -- 2.2 Notations -- 3 Related Work -- 4 Our Method -- 4.1 LSH Function -- 4.2 Distance Measure, Linear Order and Early Stop Condition -- 4.3 Index Structure -- 4.4 Search Process -- 4.5 Complexity Analysis -- 5 Experimental Results -- 5.1 Set up -- 5.2 Selection of Appropriate Parameters -- 5.3 Comparison with SK-LSH and C2LSH -- 6 Conclusion -- References -- Learning Hough Transform with Latent Structures for Joint Object Detection and Pose Estimation -- 1 Introduction -- 2 Related Work -- 3 Our Approach -- 3.1 Hough-Based Object Detection -- 3.2 Latent Deformable Feature Model -- 3.3 Multiple Instance Learning for M2HT -- 4 Experiment -- 4.1 Experiment Settings -- 4.2 Object Detection -- 4.3 Car Pose "]
[{"$nulls":4},"Estimation -- 5 Conclusion -- References -- Consensus Guided Multiple Match Removal for Geometry Verification in Image Retrieval -- 1 Introduction -- 2 Approximate Feature Matching -- 3 Geometric Verification by Hough Voting -- 4 Consensus Guided Multiple Match Removal -- 5 Experiments -- 5.1 Datasets and Evaluation -- 5.2 Experimental Setup -- 5.3 Experimental Results -- 6 Conclusion -- References -- Locality Constrained Sparse Representation for Cat Recognition -- 1 Introduction -- 2 The Methodology -- 2.1 Overview -- 2.2 Problem Formalism for Sparse Feature Representation -- 2.3 Supervised Dictionary Learning Approach -- 2.4 Recognition Task -- 3 Experimental Results -- 3.1 Dataset and Experimental Settings -- 3.2 Performance Evaluation -- 4 Conclusion and Future Work -- References -- User Profiling by Combining Topic Modeling and Pointwise Mutual Information (TM-PMI) -- Abstract -- 1 Introduction -- 2 The Proposed Approach."]
[{"$nulls":4},"2.1 Framework of the Proposed Approach -- 2.2 Data Preprocessing -- 2.3 LDA from Description of User Pins -- 2.4 Pointwise Mutual Information (PMI) -- 2.5 Personal Topic Words Extraction -- 2.6 Pins Recommended Based User Profile -- 3 Experiments -- 3.1 Dataset -- 3.2 Perplexity -- 3.3 User Study -- 3.4 Influence of the Number of Topic Words on the Result -- 4 Conclusion and Future Work -- References -- Image Retrieval Using Color-Aware Tag on Progressive Image Search and Recommendation System -- 1 Introduction -- 2 Related Works and Preliminaries -- 2.1 Related Works -- 2.2 PISAR System and WAS Algorithm -- 3 CAT Algorithm -- 3.1 Offline Phase -- 3.2 Online Phase -- 4 Experiment -- 4.1 Experimental Environment -- 4.2 Optimizing the Parameters in the CAT Algorithm -- 4.3 Example of Image Retrieval -- 4.4 Image Retrieval Result -- 5 Conclusions -- References -- Advancing Iterative Quantization Hashing Using Isotropic Prior -- 1 Introduction -- 2 Related Work -- 3 Isotropic Iterative Quantization -- 3.1 Preliminaries -- 3.2 Improving ITQ Using the Isotropic Prior -- 4 Experiments -- 5 Conclusion -- References -- An Improved RANSAC Image Stitching Algorithm Based Similarity Degree -- Abstract -- 1 Introduction -- 2 The Improved RANSAC Based Similarity Degree -- 2.1 Transformation Matrix of Image Registration -- 2.2 Calculation Method for RANSAC Sampled -- 2.3 Feature Points Matching in Coarse Matching Step -- 3 Pretreatment -- 4 Experimental Results and Analysis -- 5 Conclusions -- References -- A Novel Emotional Saliency Map to Model Emotional Attention Mechanism -- Abstract -- 1 Introduction -- 2 Emotional Saliency Map -- 2.1 Color Emotion Space -- 2.2 Emotional Saliency Map Computation -- 3 Experiments -- 3.1 Data Set and Error Measure -- 3.2 Experiments on Horror Image Set -- 3.3 Experiments on MS Image Set -- 4 Conclusion -- Acknowlegment."]
[{"$nulls":4},"References -- Automatic Endmember Extraction Using Pixel Purity Index for Hyperspectral Imagery -- Abstract -- 1 Introduction -- 2 Pixel Purity Index -- 3 Automatic Endmember Extraction Using Pixel Purity Index -- 3.1 Determining the Number of Endmembers Based on Noise Subspace Projection -- 3.2 Data Dimensionality Reduction by Improving Noise Covariance Matrix (NCM) Estimation for MNF Transformation -- 3.3 Experimental Results and Analysis -- 4 Conclusions -- Acknowledgment -- References -- A Fast 3D Indoor-Localization Approach Based on Video Queries -- 1 Introduction -- 2 Related Work -- 3 Fast 3D Indoor-Localization -- 3.1 Pipeline -- 3.2 Deblurring Query Images -- 3.3 Interactive Foreground Segmentation -- 3.4 Dynamic Scene Query for Localization -- 4 Graph Matching Verification -- 5 Experiments -- 6 Conclusion -- References -- Smart Ambient Sound Analysis via Structured Statistical Modeling -- 1 "]
[{"$nulls":4},"Introduction -- 2 Multilayer Based Ambient Sound Understanding -- 2.1 Audio Preprocessing -- 2.2 Structured Environmental Sound Modelling -- 2.3 Segment Based Adaptation -- 2.4 Audio Concept Estimation Using SVM -- 3 Experimental Configuration -- 3.1 Data Collections -- 3.2 Methodology and Evaluation Metrics -- 3.3 Competitors for Performance Comparison -- 4 Experiment Results -- 5 Conclusions -- References -- Discriminant Manifold Learning via Sparse Coding for Image Analysis -- 1 Introduction -- 2 Discriminant Manifold Learning via Sparse Coding (DML_SC) -- 2.1 Motivation -- 2.2 Dictionary Learning and Feature Regrouping -- 2.3 Graph Embedding -- 3 Experiment Results -- 3.1 Data Preparation and Representation -- 3.2 Face Recognition Results -- 3.3 Clustering Experiment on COIL20 Database -- 4 Conclusion -- References -- A Very Deep Sequences Learning Approach for Human Action Recognition -- Abstract -- 1 Introduction -- 2 Related Work."]
[{"$nulls":4},"2.1 Convolutional Neural Networks."]
[null,null,null,"Sommario/riassunto","The two-volume set LNCS 9516 and 9517 constitutes the thoroughly refereed proceedings of the 22nd International Conference on Multimedia Modeling, MMM 2016, held in Miami, FL, USA, in January 2016. The 32 revised full papers and 52 poster papers were carefully reviewed and selected from 117 submissions. In addition 20 papers were accepted for five special sessions out of 38 submissions as well as 7 demonstrations (from 11 submissions) and 9 video showcase papers. The papers are organized in topical sections on video content analysis, social media analysis, object recognition and system, multimedia retrieval and ranking, multimedia representation, machine learning in multimedia, and interaction and mobile. The special sessions are: good practices in multimedia modeling; semantics discovery from multimedia big data; perception, aesthetics, and emotion in multimedia quality modeling; multimodal learning and computing for human activity understanding; and perspectives on multimedia analytics."]