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1. |
Record Nr. |
UNISALENTO991004378028807536 |
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Autore |
Vargas Llosa, Mario |
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Titolo |
Lettere a un aspirante romanziere / Mario Vargas Llosa ; traduzione di Glauco Felici |
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Pubbl/distr/stampa |
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Titolo uniforme |
Cartas a un joven novelista 36425 |
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ISBN |
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Descrizione fisica |
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Collana |
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Einaudi Tascabili. Stile libero ; 537 |
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Altri autori (Persone) |
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Disciplina |
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Lingua di pubblicazione |
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Formato |
Materiale a stampa |
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Livello bibliografico |
Monografia |
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2. |
Record Nr. |
UNINA9911019598403321 |
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Titolo |
The ethics of cultural appropriation / / edited by James O. Young and Conrad G. Brunk |
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Pubbl/distr/stampa |
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Chichester, U.K. ; ; Malden, MA, : Wiley-Blackwell, 2009 |
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ISBN |
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9786612117374 |
9781282117372 |
1282117378 |
9781444311099 |
1444311093 |
9781444311082 |
1444311085 |
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Descrizione fisica |
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1 online resource (322 p.) |
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Altri autori (Persone) |
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YoungJames O. <1957-> |
BrunkConrad G <1945-> (Conrad Grebel) |
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Disciplina |
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Soggetti |
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Ethnic relations - Moral and ethical aspects |
Cultural property - Protection - Moral and ethical aspects |
Acculturation - Moral and ethical aspects |
Intercultural communication - Moral and ethical aspects |
Indigenous peoples - Civil rights |
Minorities - Civil rights |
Ethnic relations - Political aspects |
Cultural property - Social aspects |
Acculturation - Political aspects |
Intercultural communication - Political aspects |
Relacions ètniques |
Protecció del patrimoni cultural |
Aculturació |
Comunicació intercultural |
Aspectes morals |
Pobles indígenes |
Minories |
Drets fonamentals |
Llibres electrònics |
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Lingua di pubblicazione |
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Formato |
Materiale a stampa |
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Livello bibliografico |
Monografia |
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Note generali |
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Description based upon print version of record. |
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Nota di bibliografia |
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Includes bibliographical references and index. |
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Nota di contenuto |
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The Ethics of Cultural Appropriation; Table of Contents; Ethics of Cultural Appropriation Research Group Members; Preface; Artist Statement; 1: Introduction; 2: Archaeological Finds: Legacies of Appropriation, Modes of Response; 3: The Appropriation of Human Remains: A First Nations Legal and Ethical Perspective; 4: The Repatriation of Human Remains; 5: 'The Skin Off Our Backs' Appropriation of Religion; 6: Genetic Research and Culture: Where Does the Offense Lie?; 7: Appropriation of Traditional Knowledge: Ethics in the Context of Ethnobiology |
8: A Broken Record: Subjecting 'Music' to Cultural Rights9: Objects of Appropriation; 10: Do Subaltern Artifacts Belong in Art Museums?; 11: 'Nothing Comes from Nowhere': Reflections on Cultural Appropriation as the Representation of Other Cultures; Index |
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Sommario/riassunto |
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The Ethics of Cultural Appropriation undertakes a comprehensive and systematic investigation of the moral and aesthetic questions that arise from the practice of cultural appropriation. Explores cultural appropriation in a wide variety of contexts, among them the arts and archaeology, museums, and religionQuestions whether cultural appropriation is always morally objectionableIncludes research that is equally informed by empirical knowledge and general normative theoryProvides a coherent and authoritative perspective gained by the collaboration of p |
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3. |
Record Nr. |
UNINA9911021975803321 |
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Autore |
Gao Wei |
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Titolo |
AI-based Image and Video Coding : Methods, Standards, and Applications / / by Wei Gao |
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Pubbl/distr/stampa |
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Singapore : , : Springer Nature Singapore : , : Imprint : Springer, , 2025 |
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ISBN |
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Edizione |
[1st ed. 2025.] |
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Descrizione fisica |
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1 online resource (459 pages) |
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Disciplina |
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Soggetti |
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Coding theory |
Information theory |
Image processing |
Multimedia systems |
Virtual reality |
Augmented reality |
Computer vision |
Coding and Information Theory |
Image Processing |
Multimedia Information Systems |
Virtual and Augmented Reality |
Computer Vision |
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Lingua di pubblicazione |
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Formato |
Materiale a stampa |
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Livello bibliografico |
Monografia |
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Nota di contenuto |
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-- Chapter 1 Introduction to Image and Video Coding -- 1.1 Basic Concept of Image and Video Data -- 1.2 Representative Image and Video Datasets -- 1.3 AI-based Compression Requirement for Image and Video -- 1.4 Image and Video Coding Performance Evaluation -- 1.5 Organization of This Book -- 1.6 Summary -- Chapter 2 Fundamentals for Deep Learning-based Image and Video Coding -- 2.1 Introduction -- 2.2 Fundamental Knowledge of Deep Learning -- 2.3 Autoencoder and Variational Autoencoder -- 2.4 Principles and Framework of Deep Learning-based Image and Video Coding -- 2.5 Summary -- Chapter 3 Image and Video Quality Assessment and Perception Models -- 3.1 Introduction -- 3.2 Quality Assessment of |
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Image and Video -- 3.3 Just Noticeable Distortion of Image and Video -- 3.4 Visual Attention Modeling of Image and Video -- 3.5 Comparative Analysis -- 3.6 Summary -- Chapter 4 Deep Learning-based Image Coding -- 4.1 Introduction -- 4.2 Representative Methods of Lossless Image Coding -- 4.3 Representative Methods of Lossy Image Coding -- 4.4 Comparative Analysis -- 4.5 Summary -- Chapter 5 Deep Learning-based Video Coding -- 5.1 Introduction -- 5.2 Framework and Key Components -- 5.3 Representative Methods of Video Coding -- 5.4 Comparative Analysis -- 5.5 Summary -- Chapter 6 Deep Learning-based 3D and Multimodal Coding -- 6.1 Introduction -- 6.2 Overall Framework and Datasets -- 6.3 Representative Methods of 3D and Multimodal Coding -- 6.4 Comparative Analysis -- 6.5 Summary -- Chapter 7 Human and Machine Vision-Oriented Image and Video Coding -- 7.1 Introduction -- 7.2 Representative Methods of Human Perception-based Coding -- 7.3 Representative Methods of Machine Perception-based Coding -- 7.4 Comparative Analysis -- 7.5 Summary -- Chapter 8 Compression Artifacts Removal for Image and Video Coding -- 8.1 Introduction -- 8.2 Representative Methods of Compressed Image Artifacts Reduction -- 8.3 Representative Methods of Compressed Video Artifacts Reduction -- 8.4 Comparative Analysis -- 8.5 Summary -- Chapter 9 Deep Learning-based Image and Video Coding Standards -- 9.1 Introduction -- 9.2 Overview of International Standards -- 9.3 IEEE AI-based Image and Video Coding Standard -- 9.4 JPEG AI-based Image and Video Coding Standard -- 9.5 MPEG Video Coding for Machines Standard -- 9.6 MPAI End-to-End Video Coding Standard -- 9.7 Comparative Analysis -- 9.8 Summary -- Chapter 10 Implementations for Deep Learning-based Image and Video Coding -- 10.1 Introduction -- 10.2 Basics of Neural Network Compression -- 10.3 Software and Hardware Platforms for Acceleration -- 10.4 Lightweight Methods for Deep Compression Network -- 10.5 Comparative Analysis -- 10.6 Summary -- Chapter 11 Open Source Projects for Deep Learning-based Image and Video Coding -- 11.1 Introduction -- 11.2 Representative Open Source Projects for Image Coding -- 11.3 Representative Open Source Projects for Video Coding -- 11.4 Comparative Analysis -- 11.5 Summary -- Chapter 12 Future Works for AI-based Image and Video Coding -- 12.1 Future Work on Quality Assessment and Perception Models for Image and Video -- 12.2 Future Work on Deep Learning-based for Image Coding -- 12.3 Future Work on Deep Learning-based for Video Coding -- 12.4 Future Work on Deep Learning-based for 3D and Multimodal Coding -- 12.5 Future Work on Human and Machine Vision Oriented Image and Video Coding -- 12.6 Future Work on Compression Artifacts Removal for Image and Video Coding -- 12.7 Future Work on Deep Learning-based Image and Video Coding Standards -- 12.8 Future Work on Implementations for Deep Learning-based Image and Video Coding -- 12.9 Future Work on Open Source Projects for Deep Learning-based Image and Video Coding. |
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Sommario/riassunto |
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Unlocking the future of image and video coding with AI-based Image and Video Coding: Methods, Standards, and Applications, we can explore the revolutionary impact of deep learning technologies on image and video compression. This book is a must-read for researchers, practitioners, and students eager to stay ahead of the curve in an ever-evolving field where deep learning and artificial intelligence are setting new benchmarks in coding efficiency. With an unparalleled focus on the intersection of deep learning and multimedia coding, this book offers cutting-edge insights into the latest techniques and standards driving progress in the industry. From the |
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core principles of coding technologies to advanced topics like 3D and multimodal coding, human and machine vision-oriented compression, and compression artifacts removal, it covers all the related essentials. Special attention is given to the practical aspects of implementations, open-source projects, and standardization efforts from leading organizations like IEEE, JPEG, MPEG and MPAI. Whether you are a scholar, a professional in the multimedia industry, or a student with a foundation in computer science and electrical engineering, this book equips you with the fundamental knowledge and tools to master the latest advancements in AI-based image and video coding. You can gain a deeper understanding of how deep learning reshapes the future of image and video coding, and explore new possibilities of optimizing compression performances for both humans and machines. |
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