Deep Learning For Fluid Simulation And Animation
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Deep Learning For Fluid Simulation And Animation
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Author : Gilson Antonio Giraldi
language : en
Publisher: Springer Nature
Release Date : 2023-11-24
Deep Learning For Fluid Simulation And Animation written by Gilson Antonio Giraldi and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-11-24 with Mathematics categories.
This book is an introduction to the use of machine learning and data-driven approaches in fluid simulation and animation, as an alternative to traditional modeling techniques based on partial differential equations and numerical methods – and at a lower computational cost. This work starts with a brief review of computability theory, aimed to convince the reader – more specifically, researchers of more traditional areas of mathematical modeling – about the power of neural computing in fluid animations. In these initial chapters, fluid modeling through Navier-Stokes equations and numerical methods are also discussed. The following chapters explore the advantages of the neural networks approach and show the building blocks of neural networks for fluid simulation. They cover aspects related to training data, data augmentation, and testing. The volume completes with two case studies, one involving Lagrangian simulation of fluids using convolutional neural networks and the other using Generative Adversarial Networks (GANs) approaches.
The Art Of Fluid Animation
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Author : Jos Stam
language : en
Publisher: CRC Press
Release Date : 2015-11-04
The Art Of Fluid Animation written by Jos Stam and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-11-04 with Computers categories.
This book presents techniques for creating fluid-like animations with no required advanced physics and mathematical skills. It describes how to create fluid animations like water, smoke, fire, and explosions through computer code in a fun manner. It includes a historical background of the computation of fluids as well as concepts that drive fluid animations, and also provides computer code that readers can download and run on several platforms to create their own programs using fluid animation.
Fluid Simulation For Computer Graphics
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Author : Robert Bridson
language : en
Publisher: CRC Press
Release Date : 2015-09-18
Fluid Simulation For Computer Graphics written by Robert Bridson and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-09-18 with Computers categories.
A practical introduction, the second edition of Fluid Simulation for Computer Graphics shows you how to animate fully three-dimensional incompressible flow. It covers all the aspects of fluid simulation, from the mathematics and algorithms to implementation, while making revisions and updates to reflect changes in the field since the first edition. Highlights of the Second Edition New chapters on level sets and vortex methods Emphasizes hybrid particle–voxel methods, now the industry standard approach Covers the latest algorithms and techniques, including: fluid surface reconstruction from particles; accurate, viscous free surfaces for buckling, coiling, and rotating liquids; and enhanced turbulence for smoke animation Adds new discussions on meshing, particles, and vortex methods The book changes the order of topics as they appeared in the first edition to make more sense when reading the first time through. It also contains several updates by distilling author Robert Bridson’s experience in the visual effects industry to highlight the most important points in fluid simulation. It gives you an understanding of how the components of fluid simulation work as well as the tools for creating your own animations.
Modern Machine Learning Techniques And Their Applications In Cartoon Animation Research
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Author : Jun Yu
language : en
Publisher: John Wiley & Sons
Release Date : 2013-03-18
Modern Machine Learning Techniques And Their Applications In Cartoon Animation Research written by Jun Yu and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-03-18 with Computers categories.
The integration of machine learning techniques and cartoon animation research is fast becoming a hot topic. This book helps readers learn the latest machine learning techniques, including patch alignment framework; spectral clustering, graph cuts, and convex relaxation; ensemble manifold learning; multiple kernel learning; multiview subspace learning; and multiview distance metric learning. It then presents the applications of these modern machine learning techniques in cartoon animation research. With these techniques, users can efficiently utilize the cartoon materials to generate animations in areas such as virtual reality, video games, animation films, and sport simulations
Computer Animation And Social Agents
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Author : Nadia Magnenat Thalmann
language : en
Publisher: Springer Nature
Release Date : 2025-03-08
Computer Animation And Social Agents written by Nadia Magnenat Thalmann and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-03-08 with Computers categories.
This two-volume set, CCIS 2374 and CCIS 2375, constitutes the revised selected papers from the 37th International Conference on Computer Animation and Social Agents, CASA 2024, held in Wuhan, China, during June 5-7, 2024. The 60 papers presented in these two volumes were carefully reviewed and selected from 208 submissions. These papers focus on various aspects of Computer Animation and Social Agents, such as Motion Capture & Retargeting, Physics-based Animation, Vision-based Techniques, Behavioral Animation, Facial Animation, Image-based Animation, Virtual Humans, Crowd Simulation, AI-based Animation, Deep Learning methods, Virtual humans and avatars, and 3D Physiological Humans.
Knowledge Guided Machine Learning
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Author : Anuj Karpatne
language : en
Publisher: CRC Press
Release Date : 2022-08-15
Knowledge Guided Machine Learning written by Anuj Karpatne and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-08-15 with Business & Economics categories.
Given their tremendous success in commercial applications, machine learning (ML) models are increasingly being considered as alternatives to science-based models in many disciplines. Yet, these "black-box" ML models have found limited success due to their inability to work well in the presence of limited training data and generalize to unseen scenarios. As a result, there is a growing interest in the scientific community on creating a new generation of methods that integrate scientific knowledge in ML frameworks. This emerging field, called scientific knowledge-guided ML (KGML), seeks a distinct departure from existing "data-only" or "scientific knowledge-only" methods to use knowledge and data at an equal footing. Indeed, KGML involves diverse scientific and ML communities, where researchers and practitioners from various backgrounds and application domains are continually adding richness to the problem formulations and research methods in this emerging field. Knowledge Guided Machine Learning: Accelerating Discovery using Scientific Knowledge and Data provides an introduction to this rapidly growing field by discussing some of the common themes of research in KGML using illustrative examples, case studies, and reviews from diverse application domains and research communities as book chapters by leading researchers. KEY FEATURES First-of-its-kind book in an emerging area of research that is gaining widespread attention in the scientific and data science fields Accessible to a broad audience in data science and scientific and engineering fields Provides a coherent organizational structure to the problem formulations and research methods in the emerging field of KGML using illustrative examples from diverse application domains Contains chapters by leading researchers, which illustrate the cutting-edge research trends, opportunities, and challenges in KGML research from multiple perspectives Enables cross-pollination of KGML problem formulations and research methods across disciplines Highlights critical gaps that require further investigation by the broader community of researchers and practitioners to realize the full potential of KGML
Computer Animation And Social Agents
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Author : Feng Tian
language : en
Publisher: Springer Nature
Release Date : 2020-11-25
Computer Animation And Social Agents written by Feng Tian and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-11-25 with Computers categories.
This book constitutes the revised selected papers of the 33rd International Conference on Computer Animation and Social Agents, CASA 2020, held in Bournemouth, UK*, in October 2020. The 1 full paper and 13 short papers presented were carefully reviewed and selected from a total of 86 submissions. The papers are organized in topical sections of modelling, animation and simulation; virtual reality; image processing and computer vision. *The conference was held virtually due to the COVID-19 pandemic.
Computational Mechanics With Neural Networks
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Author : Genki Yagawa
language : en
Publisher: Springer Nature
Release Date : 2021-02-26
Computational Mechanics With Neural Networks written by Genki Yagawa and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-02-26 with Technology & Engineering categories.
This book shows how neural networks are applied to computational mechanics. Part I presents the fundamentals of neural networks and other machine learning method in computational mechanics. Part II highlights the applications of neural networks to a variety of problems of computational mechanics. The final chapter gives perspectives to the applications of the deep learning to computational mechanics.
Advances In Computer Graphics
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Author : Nadia Magnenat-Thalmann
language : en
Publisher: Springer Nature
Release Date : 2023-01-01
Advances In Computer Graphics written by Nadia Magnenat-Thalmann and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-01-01 with Computers categories.
This book constitutes the refereed proceedings of the 39th Computer Graphics International Conference on Advances in Computer Graphics, CGI 2022, held Virtually, during September 12–16, 2022. The 45 full papers included in this book were carefully reviewed and selected from 139 submissions. They were organized in topical sections as follows: image analysis & processing; graphs & networks; estimation & feature matching; 3d reconstruction; rendering & animation; detection & recognition; colors, paintings & layout; synthesis & generation; ar & user interfaces; medical imaging; segmentation; object detection; image attention & perception; and modeling & simulation.
Computational Science Iccs 2025 Workshops
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Author : Maciej Paszynski
language : en
Publisher: Springer Nature
Release Date : 2025-07-06
Computational Science Iccs 2025 Workshops written by Maciej Paszynski and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-07-06 with Computers categories.
The 6-volume set constitutes the workshop proceedings of the 25th International Conference on Computational Science, ICCS 2025, which took place in Singapore, Singapore, during July 7–9, 2025. The 137 full papers and 32 short papers presented in these proceedings were carefully reviewed and selected from 322 submissions. The papers are organized in the following topical sections: Volume I: Advances in high-performance computational earth sciences: numerical methods, frameworks & applications; artificial intelligence approaches for network analysis; artificial intelligence and high-performance computing for advanced simulations; and biomedical and bioinformatics challenges for computer science. Volume II: Computational health; computational modeling and artificial intelligence for social systems; and computational optimization, modelling and simulation. Volume III: Computational science and AI for addressing complex and dynamic societal challenges equitably; computer graphics, image processing and artificial intelligence; computing and data science for materials discovery and design; and large language models and intelligent decision-making within the digital economy. Volume IV: Machine learning and data assimilation for dynamical systems; and multi-criteria decision-making: methods, applications, and innovations. Volume V: (Credible) Multiscale modelling and simulation; numerical algorithms and computer arithmetic for computational science; quantum computing; retrieval-augmented generation; and simulations of flow and transport: modeling, algorithms and computation. Volume VI: Smart systems: bringing together computer vision, sensor networks and artificial intelligence; solving problems with uncertainty; and teaching computational science.